{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:04.921233Z",
     "end_time": "2024-05-23T11:29:06.227658Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 第3章 数据探索\n",
    "### 3.1 数据质量分析\n",
    "#### 3.1.1 缺失值分析\n",
    "##### 1. 缺失值产生的原因\n",
    "##### 2. 缺失值的影响\n",
    "##### 3. 缺失值分析\n",
    "#### 3.1.2 异常值分析\n",
    "##### 1. 简单统计量分析\n",
    "##### 2. 3$\\sigma$原则\n",
    "##### 3. 箱形图分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.226651Z",
     "end_time": "2024-05-23T11:29:06.285679Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "201"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用describe()方法查看数据的基本情况\n",
    "data = pd.read_excel('./data/catering_sale.xls', index_col='日期')\n",
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "                销量\ncount   200.000000\nmean   2768.050700\nstd     726.103877\nmin      22.000000\n25%    2452.975000\n50%    2655.850000\n75%    3026.125000\nmax    9106.440000",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>销量</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>200.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2768.050700</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>726.103877</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>22.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>2452.975000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>2655.850000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>3026.125000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>9106.440000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.272522Z",
     "end_time": "2024-05-23T11:29:06.287681Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 餐饮日销额数据异常值检测\n",
    "plt.figure()\n",
    "p = data.boxplot(return_type='dict')\n",
    "x = p['fliers'][0].get_xdata()  # 'flies'即为异常值的标签\n",
    "y = p['fliers'][0].get_ydata()\n",
    "y.sort()  # 从小到大排序，该方法直接改变原对象\n",
    "'''\n",
    "用annotate添加注释\n",
    "其中有些相近的点，注解会出现重叠，难以看清，需要一些技巧来控制\n",
    "以下参数都是经过调试的，需要具体问题具体调试。\n",
    "'''\n",
    "for i in range(len(x)):\n",
    "    if i > 0:\n",
    "        plt.annotate(y[i], xy=(x[i], y[i]), xytext=(x[i] + 0.05 - 0.8 / (y[i] - y[i - 1]), y[i]))\n",
    "    else:\n",
    "        plt.annotate(y[i], xy=(x[i], y[i]), xytext=(x[i] + 0.08, y[i]))\n",
    "\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.290681Z",
     "end_time": "2024-05-23T11:29:06.645467Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.1.3 一致性分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 3.2 数据特性分析\n",
    "#### 3.2.1 分布分析\n",
    "##### 1. 定量数据的分布分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x600 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# “捞起生鱼片”的季度销售情况\n",
    "data = pd.read_excel('./data/catering_fish_congee.xls', names=['date', 'sale'])\n",
    "d = 500\n",
    "num_bins = round((max(data['sale']) - min(data['sale'])) / d)\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(data['sale'], num_bins)\n",
    "plt.xticks(range(0, 4000, d))\n",
    "plt.xlabel('sale分层')\n",
    "plt.grid()\n",
    "plt.title('季度销售额频率分布直方图', fontsize=20)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.524441Z",
     "end_time": "2024-05-23T11:29:07.168827Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "##### 2. 定性数据的分布分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x600 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 不同菜品在某段时间的销售量分布情况\n",
    "data = pd.read_excel('./data/catering_dish_profit.xls')\n",
    "x = data['盈利']\n",
    "labels = data['菜品名']\n",
    "plt.figure(figsize=(8, 6))  # 设置画布大小\n",
    "plt.pie(x, labels=labels)  # 绘制饼图\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'\n",
    "plt.title('菜品销售量分布（饼图）')  # 设置标题\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.678400Z",
     "end_time": "2024-05-23T11:29:07.201833Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x400 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 不同菜品在某段时间的销售量分布情况\n",
    "x = data['菜品名']\n",
    "y = data['盈利']\n",
    "plt.figure(figsize=(8, 4))  # 设置画布大小\n",
    "plt.bar(x, y)\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'\n",
    "plt.xlabel('菜品')  # 设置x轴标题\n",
    "plt.ylabel('销量')  # 设置y轴标题\n",
    "plt.title('菜品销售量分布（条形图）')  # 设置标题\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.829167Z",
     "end_time": "2024-05-23T11:29:07.202836Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.2.2 对比分析\n",
    "##### 1. 绝对数比较\n",
    "##### 2. 相对数比较"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "     月份   A部门   B部门  C部门\n0    1月  8.00  7.70  5.3\n1    2月  6.00  6.50  5.2\n2    3月  6.89  7.90  5.8\n3    4月  6.10  7.50  6.2\n4    5月  6.05  8.00  5.9\n5    6月  6.01  7.40  5.5\n6    7月  6.60  7.50  6.1\n7    8月  6.40  7.00  5.7\n8    9月  5.80  7.20  5.4\n9   10月  6.70  6.60  5.5\n10  11月  6.60  6.65  5.6\n11  12月  5.30  5.40  5.2",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>月份</th>\n      <th>A部门</th>\n      <th>B部门</th>\n      <th>C部门</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1月</td>\n      <td>8.00</td>\n      <td>7.70</td>\n      <td>5.3</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2月</td>\n      <td>6.00</td>\n      <td>6.50</td>\n      <td>5.2</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3月</td>\n      <td>6.89</td>\n      <td>7.90</td>\n      <td>5.8</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4月</td>\n      <td>6.10</td>\n      <td>7.50</td>\n      <td>6.2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5月</td>\n      <td>6.05</td>\n      <td>8.00</td>\n      <td>5.9</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6月</td>\n      <td>6.01</td>\n      <td>7.40</td>\n      <td>5.5</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7月</td>\n      <td>6.60</td>\n      <td>7.50</td>\n      <td>6.1</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8月</td>\n      <td>6.40</td>\n      <td>7.00</td>\n      <td>5.7</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9月</td>\n      <td>5.80</td>\n      <td>7.20</td>\n      <td>5.4</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10月</td>\n      <td>6.70</td>\n      <td>6.60</td>\n      <td>5.5</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>11月</td>\n      <td>6.60</td>\n      <td>6.65</td>\n      <td>5.6</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>12月</td>\n      <td>5.30</td>\n      <td>5.40</td>\n      <td>5.2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 部门间销售金额比较\n",
    "data = pd.read_excel('./data/dish_sale.xls')\n",
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.964503Z",
     "end_time": "2024-05-23T11:29:07.211836Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x400 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.plot(data['月份'], data['A部门'], color='green', label='A部门', marker='o')\n",
    "plt.plot(data['月份'], data['B部门'], color='red', label='B部门', marker='s')\n",
    "plt.plot(data['月份'], data['C部门'], color='skyblue', label='C部门', marker='x')\n",
    "plt.legend()\n",
    "plt.ylabel('销售额（万元）')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:06.986437Z",
     "end_time": "2024-05-23T11:29:07.213835Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "     月份  2014年  2013年  2012年\n0    1月   7.90   7.70    5.3\n1    2月   6.00   6.50    5.2\n2    3月   6.89   7.90    5.8\n3    4月   7.30   7.50    6.2\n4    5月   7.60   8.00    5.9\n5    6月   7.20   7.40    5.5\n6    7月   7.40   7.50    6.1\n7    8月   7.80   7.00    5.7\n8    9月   7.00   7.20    5.4\n9   10月   6.70   6.60    5.5\n10  11月   6.60   6.65    5.6\n11  12月   6.30   6.40    5.2",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>月份</th>\n      <th>2014年</th>\n      <th>2013年</th>\n      <th>2012年</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1月</td>\n      <td>7.90</td>\n      <td>7.70</td>\n      <td>5.3</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2月</td>\n      <td>6.00</td>\n      <td>6.50</td>\n      <td>5.2</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3月</td>\n      <td>6.89</td>\n      <td>7.90</td>\n      <td>5.8</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4月</td>\n      <td>7.30</td>\n      <td>7.50</td>\n      <td>6.2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5月</td>\n      <td>7.60</td>\n      <td>8.00</td>\n      <td>5.9</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6月</td>\n      <td>7.20</td>\n      <td>7.40</td>\n      <td>5.5</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7月</td>\n      <td>7.40</td>\n      <td>7.50</td>\n      <td>6.1</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8月</td>\n      <td>7.80</td>\n      <td>7.00</td>\n      <td>5.7</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9月</td>\n      <td>7.00</td>\n      <td>7.20</td>\n      <td>5.4</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10月</td>\n      <td>6.70</td>\n      <td>6.60</td>\n      <td>5.5</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>11月</td>\n      <td>6.60</td>\n      <td>6.65</td>\n      <td>5.6</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>12月</td>\n      <td>6.30</td>\n      <td>6.40</td>\n      <td>5.2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B部门各年份间销售金额的比较\n",
    "data = pd.read_excel('./data/dish_sale_b.xls')\n",
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.134969Z",
     "end_time": "2024-05-23T11:29:07.214836Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x400 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.plot(data['月份'], data['2012年'], color='green', label='2012年', marker='o')\n",
    "plt.plot(data['月份'], data['2013年'], color='red', label='2013年', marker='s')\n",
    "plt.plot(data['月份'], data['2014年'], color='skyblue', label='2014年', marker='x')\n",
    "plt.legend()\n",
    "plt.ylabel('销售额（万元）')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.151822Z",
     "end_time": "2024-05-23T11:29:07.465282Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.2.3 统计量分析\n",
    "##### 1. 集中趋势度量\n",
    "##### 2. 离中趋势度量"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "                销量\n日期                \n2015-03-01  2618.2\n2015-02-28  2618.2\n2015-02-27  2608.4\n2015-02-26  2651.9\n2015-02-25  3442.1\n...            ...\n2014-08-06  2915.8\n2014-08-05  2618.1\n2014-08-04  2993.0\n2014-08-03  3436.4\n2014-08-02  2261.7\n\n[201 rows x 1 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>销量</th>\n    </tr>\n    <tr>\n      <th>日期</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2015-03-01</th>\n      <td>2618.2</td>\n    </tr>\n    <tr>\n      <th>2015-02-28</th>\n      <td>2618.2</td>\n    </tr>\n    <tr>\n      <th>2015-02-27</th>\n      <td>2608.4</td>\n    </tr>\n    <tr>\n      <th>2015-02-26</th>\n      <td>2651.9</td>\n    </tr>\n    <tr>\n      <th>2015-02-25</th>\n      <td>3442.1</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>2014-08-06</th>\n      <td>2915.8</td>\n    </tr>\n    <tr>\n      <th>2014-08-05</th>\n      <td>2618.1</td>\n    </tr>\n    <tr>\n      <th>2014-08-04</th>\n      <td>2993.0</td>\n    </tr>\n    <tr>\n      <th>2014-08-03</th>\n      <td>3436.4</td>\n    </tr>\n    <tr>\n      <th>2014-08-02</th>\n      <td>2261.7</td>\n    </tr>\n  </tbody>\n</table>\n<p>201 rows × 1 columns</p>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('./data/catering_sale.xls', index_col='日期')\n",
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.324058Z",
     "end_time": "2024-05-23T11:29:07.466282Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "                销量\ncount   196.000000\nmean   2743.950510\nstd     423.745120\nmin     865.000000\n25%    2464.350000\n50%    2655.850000\n75%    3022.900000\nmax    4065.200000\nrange  3200.200000\nvar       0.154429\ndis     558.550000",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>销量</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>196.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2743.950510</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>423.745120</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>865.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>2464.350000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>2655.850000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>3022.900000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>4065.200000</td>\n    </tr>\n    <tr>\n      <th>range</th>\n      <td>3200.200000</td>\n    </tr>\n    <tr>\n      <th>var</th>\n      <td>0.154429</td>\n    </tr>\n    <tr>\n      <th>dis</th>\n      <td>558.550000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = data[(data['销量'] > 400) & (data['销量'] < 5000)]  #过滤异常数据\n",
    "statistics = data.describe()\n",
    "statistics.loc['range'] = statistics.loc['max'] - statistics.loc['min']  #极差\n",
    "statistics.loc['var'] = statistics.loc['std'] / statistics.loc['mean']  #变异系数\n",
    "statistics.loc['dis'] = statistics.loc['75%'] - statistics.loc['25%']  #四分位数间距\n",
    "statistics"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.340702Z",
     "end_time": "2024-05-23T11:29:07.520298Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.2.4 周期性分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "         Date  Eletricity\n0    2012/2/1        6200\n1    2012/2/2        6440\n2    2012/2/3        6440\n3    2012/2/4        4293\n4    2012/2/5        2146\n5    2012/2/6        6490\n6    2012/2/7        6320\n7    2012/2/8        6820\n8    2012/2/9        6960\n9   2012/2/10        7200\n10  2012/2/11        4123\n11  2012/2/12        2444\n12  2012/2/13        6880\n13  2012/2/14        7210\n14  2012/2/15        7300\n15  2012/2/16        7360\n16  2012/2/17        7060\n17  2012/2/18        5123\n18  2012/2/19        2044\n19  2012/2/20        6920\n20  2012/2/21        7070\n21  2012/2/22        6910\n22  2012/2/23        7080\n23  2012/2/24        7190\n24  2012/2/25        6534\n25  2012/2/26        4532\n26  2012/2/27        7310\n27  2012/2/28        7330\n28  2012/2/29        7130\n29   2012/3/1        7370\n30   2012/3/2        7250\n31   2012/3/3        4833\n32   2012/3/4        2416\n33   2012/3/5        7090\n34   2012/3/6        7110\n35   2012/3/7        7020\n36   2012/3/8        6670\n37   2012/3/9        6790\n38  2012/3/10        3425\n39  2012/3/11        3256\n40  2012/3/12        6730\n41  2012/3/13        7280\n42  2012/3/14        7190\n43  2012/3/15        7260\n44  2012/3/16        7340\n45  2012/3/17        7231\n46  2012/3/18        7023\n47  2012/3/19        7310\n48  2012/3/20        7230\n49  2012/3/21        7260\n50  2012/3/22        7190\n51  2012/3/23        7130\n52  2012/3/24        5683\n53  2012/3/25        2343\n54  2012/3/26        7480\n55  2012/3/27        7210\n56  2012/3/28        7280\n57  2012/3/29        7280\n58  2012/3/30        7150",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Date</th>\n      <th>Eletricity</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2012/2/1</td>\n      <td>6200</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2012/2/2</td>\n      <td>6440</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2012/2/3</td>\n      <td>6440</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2012/2/4</td>\n      <td>4293</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2012/2/5</td>\n      <td>2146</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2012/2/6</td>\n      <td>6490</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2012/2/7</td>\n      <td>6320</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2012/2/8</td>\n      <td>6820</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2012/2/9</td>\n      <td>6960</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2012/2/10</td>\n      <td>7200</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2012/2/11</td>\n      <td>4123</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>2012/2/12</td>\n      <td>2444</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>2012/2/13</td>\n      <td>6880</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>2012/2/14</td>\n      <td>7210</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>2012/2/15</td>\n      <td>7300</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2012/2/16</td>\n      <td>7360</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2012/2/17</td>\n      <td>7060</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2012/2/18</td>\n      <td>5123</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2012/2/19</td>\n      <td>2044</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2012/2/20</td>\n      <td>6920</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2012/2/21</td>\n      <td>7070</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2012/2/22</td>\n      <td>6910</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2012/2/23</td>\n      <td>7080</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>2012/2/24</td>\n      <td>7190</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>2012/2/25</td>\n      <td>6534</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>2012/2/26</td>\n      <td>4532</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>2012/2/27</td>\n      <td>7310</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>2012/2/28</td>\n      <td>7330</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>2012/2/29</td>\n      <td>7130</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>2012/3/1</td>\n      <td>7370</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>2012/3/2</td>\n      <td>7250</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>2012/3/3</td>\n      <td>4833</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>2012/3/4</td>\n      <td>2416</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>2012/3/5</td>\n      <td>7090</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>2012/3/6</td>\n      <td>7110</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>2012/3/7</td>\n      <td>7020</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>2012/3/8</td>\n      <td>6670</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>2012/3/9</td>\n      <td>6790</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>2012/3/10</td>\n      <td>3425</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>2012/3/11</td>\n      <td>3256</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>2012/3/12</td>\n      <td>6730</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>2012/3/13</td>\n      <td>7280</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>2012/3/14</td>\n      <td>7190</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>2012/3/15</td>\n      <td>7260</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>2012/3/16</td>\n      <td>7340</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>2012/3/17</td>\n      <td>7231</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>2012/3/18</td>\n      <td>7023</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>2012/3/19</td>\n      <td>7310</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>2012/3/20</td>\n      <td>7230</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>2012/3/21</td>\n      <td>7260</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>2012/3/22</td>\n      <td>7190</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>2012/3/23</td>\n      <td>7130</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>2012/3/24</td>\n      <td>5683</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>2012/3/25</td>\n      <td>2343</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td>2012/3/26</td>\n      <td>7480</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>2012/3/27</td>\n      <td>7210</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>2012/3/28</td>\n      <td>7280</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>2012/3/29</td>\n      <td>7280</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>2012/3/30</td>\n      <td>7150</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_normal = pd.read_csv('./data/user.csv')\n",
    "df_normal"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.377126Z",
     "end_time": "2024-05-23T11:29:07.569683Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x400 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.plot(df_normal['Date'], df_normal['Eletricity'])\n",
    "plt.xlabel('日期')\n",
    "x_major_locator = plt.MultipleLocator(7)\n",
    "ax = plt.gca()\n",
    "ax.xaxis.set_major_locator(x_major_locator)\n",
    "plt.ylabel('每日电量')\n",
    "plt.title('正常用户电量趋势')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.393267Z",
     "end_time": "2024-05-23T11:29:07.825108Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "         Date  Eletricity\n0    2012/2/1        6100\n1    2012/2/2        6312\n2    2012/2/3        6240\n3    2012/2/4        4293\n4    2012/2/5        3346\n5    2012/2/6        6390\n6    2012/2/7        6170\n7    2012/2/8        6720\n8    2012/2/9        6850\n9   2012/2/10        7000\n10  2012/2/11        2123\n11  2012/2/12        1344\n12  2012/2/13        5680\n13  2012/2/14        5910\n14  2012/2/15        5950\n15  2012/2/16        6000\n16  2012/2/17        5681\n17  2012/2/18        3743\n18  2012/2/19         660\n19  2012/2/20        5530\n20  2012/2/21        5070\n21  2012/2/22        4810\n22  2012/2/23        4880\n23  2012/2/24        4790\n24  2012/2/25        4078\n25  2012/2/26        1965\n26  2012/2/27        4601\n27  2012/2/28        4531\n28  2012/2/29        4263\n29   2012/3/1        4471\n30   2012/3/2        4750\n31   2012/3/3        3963\n32   2012/3/4        1509\n33   2012/3/5        4090\n34   2012/3/6        4001\n35   2012/3/7        3737\n36   2012/3/8        3203\n37   2012/3/9        3312\n38  2012/3/10         935\n39  2012/3/11        2756\n40  2012/3/12        3230\n41  2012/3/13        2702\n42  2012/3/14        2567\n43  2012/3/15         571\n44  2012/3/16        2307\n45  2012/3/17        2230\n46  2012/3/18        1945\n47  2012/3/19        2220\n48  2012/3/20        2041\n49  2012/3/21        2060\n50  2012/3/22        2000\n51  2012/3/23        1821\n52  2012/3/24        1800\n53  2012/3/25        1745\n54  2012/3/26        1023\n55  2012/3/27        2045\n56  2012/3/28        2132\n57  2012/3/29        2345\n58  2012/3/30        2267",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Date</th>\n      <th>Eletricity</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2012/2/1</td>\n      <td>6100</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2012/2/2</td>\n      <td>6312</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2012/2/3</td>\n      <td>6240</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2012/2/4</td>\n      <td>4293</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2012/2/5</td>\n      <td>3346</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2012/2/6</td>\n      <td>6390</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2012/2/7</td>\n      <td>6170</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2012/2/8</td>\n      <td>6720</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2012/2/9</td>\n      <td>6850</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2012/2/10</td>\n      <td>7000</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2012/2/11</td>\n      <td>2123</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>2012/2/12</td>\n      <td>1344</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>2012/2/13</td>\n      <td>5680</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>2012/2/14</td>\n      <td>5910</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>2012/2/15</td>\n      <td>5950</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2012/2/16</td>\n      <td>6000</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2012/2/17</td>\n      <td>5681</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2012/2/18</td>\n      <td>3743</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2012/2/19</td>\n      <td>660</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2012/2/20</td>\n      <td>5530</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2012/2/21</td>\n      <td>5070</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2012/2/22</td>\n      <td>4810</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2012/2/23</td>\n      <td>4880</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>2012/2/24</td>\n      <td>4790</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>2012/2/25</td>\n      <td>4078</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>2012/2/26</td>\n      <td>1965</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>2012/2/27</td>\n      <td>4601</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>2012/2/28</td>\n      <td>4531</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>2012/2/29</td>\n      <td>4263</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>2012/3/1</td>\n      <td>4471</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>2012/3/2</td>\n      <td>4750</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>2012/3/3</td>\n      <td>3963</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>2012/3/4</td>\n      <td>1509</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>2012/3/5</td>\n      <td>4090</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>2012/3/6</td>\n      <td>4001</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>2012/3/7</td>\n      <td>3737</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>2012/3/8</td>\n      <td>3203</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>2012/3/9</td>\n      <td>3312</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>2012/3/10</td>\n      <td>935</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>2012/3/11</td>\n      <td>2756</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>2012/3/12</td>\n      <td>3230</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>2012/3/13</td>\n      <td>2702</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>2012/3/14</td>\n      <td>2567</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>2012/3/15</td>\n      <td>571</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>2012/3/16</td>\n      <td>2307</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>2012/3/17</td>\n      <td>2230</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>2012/3/18</td>\n      <td>1945</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>2012/3/19</td>\n      <td>2220</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>2012/3/20</td>\n      <td>2041</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>2012/3/21</td>\n      <td>2060</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>2012/3/22</td>\n      <td>2000</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>2012/3/23</td>\n      <td>1821</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>2012/3/24</td>\n      <td>1800</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>2012/3/25</td>\n      <td>1745</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td>2012/3/26</td>\n      <td>1023</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>2012/3/27</td>\n      <td>2045</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>2012/3/28</td>\n      <td>2132</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>2012/3/29</td>\n      <td>2345</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>2012/3/30</td>\n      <td>2267</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_steal = pd.read_csv('./data/Steal user.csv')\n",
    "df_steal"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.545296Z",
     "end_time": "2024-05-23T11:29:07.825108Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x400 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.plot(df_steal['Date'], df_steal['Eletricity'])\n",
    "plt.xlabel('日期')\n",
    "x_major_locator = plt.MultipleLocator(7)\n",
    "ax = plt.gca()\n",
    "ax.xaxis.set_major_locator(x_major_locator)\n",
    "plt.ylabel('每日电量')\n",
    "plt.title('窃电用户电量趋势')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.561679Z",
     "end_time": "2024-05-23T11:29:07.895141Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.2.5 贡献度分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "菜品名\nA1     9173\nA2     5729\nA3     4811\nA4     3594\nA5     3195\nA6     3026\nA7     2378\nA8     1970\nA9     1877\nA10    1782\nName: 盈利, dtype: int64"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('./data/catering_dish_profit.xls', index_col='菜品名')\n",
    "data = data['盈利'].copy()\n",
    "data.sort_values(ascending=False)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.718002Z",
     "end_time": "2024-05-23T11:29:08.035654Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "data.plot(kind='bar')\n",
    "plt.ylabel('盈利（元）')\n",
    "p = 1.0 * data.cumsum() / data.sum()\n",
    "p.plot(color='r', secondary_y=True, style='-o', linewidth=2)\n",
    "plt.annotate(format(p.iloc[6], '.0%'), xy=(6, p.iloc[6]), xytext=(6 * 1.1, p.iloc[6] * 0.9),\n",
    "             arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=.2'))\n",
    "plt.ylabel('盈利（比例）')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.733088Z",
     "end_time": "2024-05-23T11:29:08.254473Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.2.6 相关性分析\n",
    "##### 1. 直接绘制散点图\n",
    "##### 2. 绘制散点图矩阵\n",
    "##### 3. 计算相关系数"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "            百合酱蒸凤爪  翡翠蒸香茜饺  金银蒜汁蒸排骨  乐膳真味鸡  蜜汁焗餐包  生炒菜心  铁板酸菜豆腐  香煎韭菜饺  香煎罗卜糕  \\\n日期                                                                              \n2015-01-01      17       6        8     24   13.0    13      18     10     10   \n2015-01-02      11      15       14     13    9.0    10      19     13     14   \n2015-01-03      10       8       12     13    8.0     3       7     11     10   \n2015-01-04       9       6        6      3   10.0     9       9     13     14   \n2015-01-05       4      10       13      8   12.0    10      17     11     13   \n2015-01-06      13      10       13     16    8.0     9      12     11      5   \n2015-01-07       9       7       13      8    5.0     7      10      8     10   \n2015-01-08       9      12       13      6    7.0     8       6     12     11   \n2015-01-12       6       8        8      3    NaN     4       5      5      7   \n2015-01-13       9      11       13      6    8.0     7       6      9      8   \n2015-01-14       6       7        8      9    4.0     7       8      5      3   \n2015-01-15       5       9        4      7    8.0     9      15      9     13   \n2015-01-16       9       7       11      9   11.0     8      14      9      9   \n2015-01-17      10       8       10      6   14.0    13      16      9      4   \n2015-01-18      13      12       12     10    9.0    11       8     12      9   \n2015-01-19       4       8       12     11    9.0     7      10      6     11   \n2015-01-20       6      12       10      9   11.0     4       8     14      6   \n2015-01-21       9      15        4     12    7.0     9       1      5     12   \n2015-01-22       3      10       13     13   13.0     8      13      5     11   \n2015-01-23       8       7        9     20    5.0    12       8      7      8   \n2015-01-24      11       6       11      8    7.0     8       9      7     10   \n2015-01-25      11       6        5     15    7.0    14      14      7      6   \n2015-01-26       4       7       10      7    6.0    10       9     12      7   \n2015-01-27       7       5        6      7   12.0    15       6     12      9   \n2015-01-28       8       8       12     14    8.0    11       7     12     10   \n2015-01-29       4      10       12      9    7.0     8       8     10     10   \n2015-01-30       6       7        7     11    7.0     7       9     16     10   \n2015-01-31       8       5       11     10    8.0    11       8     10     10   \n2015-02-01       8       6        7      9    6.0     4       6     11      6   \n\n            原汁原味菜心  \n日期                  \n2015-01-01      27  \n2015-01-02      13  \n2015-01-03       9  \n2015-01-04      13  \n2015-01-05      14  \n2015-01-06       9  \n2015-01-07       7  \n2015-01-08       5  \n2015-01-12      10  \n2015-01-13       9  \n2015-01-14      10  \n2015-01-15       9  \n2015-01-16      15  \n2015-01-17      14  \n2015-01-18      15  \n2015-01-19      11  \n2015-01-20      13  \n2015-01-21       8  \n2015-01-22      11  \n2015-01-23      11  \n2015-01-24       9  \n2015-01-25       8  \n2015-01-26       5  \n2015-01-27       4  \n2015-01-28       6  \n2015-01-29      11  \n2015-01-30      11  \n2015-01-31       9  \n2015-02-01       9  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>百合酱蒸凤爪</th>\n      <th>翡翠蒸香茜饺</th>\n      <th>金银蒜汁蒸排骨</th>\n      <th>乐膳真味鸡</th>\n      <th>蜜汁焗餐包</th>\n      <th>生炒菜心</th>\n      <th>铁板酸菜豆腐</th>\n      <th>香煎韭菜饺</th>\n      <th>香煎罗卜糕</th>\n      <th>原汁原味菜心</th>\n    </tr>\n    <tr>\n      <th>日期</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2015-01-01</th>\n      <td>17</td>\n      <td>6</td>\n      <td>8</td>\n      <td>24</td>\n      <td>13.0</td>\n      <td>13</td>\n      <td>18</td>\n      <td>10</td>\n      <td>10</td>\n      <td>27</td>\n    </tr>\n    <tr>\n      <th>2015-01-02</th>\n      <td>11</td>\n      <td>15</td>\n      <td>14</td>\n      <td>13</td>\n      <td>9.0</td>\n      <td>10</td>\n      <td>19</td>\n      <td>13</td>\n      <td>14</td>\n      <td>13</td>\n    </tr>\n    <tr>\n      <th>2015-01-03</th>\n      <td>10</td>\n      <td>8</td>\n      <td>12</td>\n      <td>13</td>\n      <td>8.0</td>\n      <td>3</td>\n      <td>7</td>\n      <td>11</td>\n      <td>10</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2015-01-04</th>\n      <td>9</td>\n      <td>6</td>\n      <td>6</td>\n      <td>3</td>\n      <td>10.0</td>\n      <td>9</td>\n      <td>9</td>\n      <td>13</td>\n      <td>14</td>\n      <td>13</td>\n    </tr>\n    <tr>\n      <th>2015-01-05</th>\n      <td>4</td>\n      <td>10</td>\n      <td>13</td>\n      <td>8</td>\n      <td>12.0</td>\n      <td>10</td>\n      <td>17</td>\n      <td>11</td>\n      <td>13</td>\n      <td>14</td>\n    </tr>\n    <tr>\n      <th>2015-01-06</th>\n      <td>13</td>\n      <td>10</td>\n      <td>13</td>\n      <td>16</td>\n      <td>8.0</td>\n      <td>9</td>\n      <td>12</td>\n      <td>11</td>\n      <td>5</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2015-01-07</th>\n      <td>9</td>\n      <td>7</td>\n      <td>13</td>\n      <td>8</td>\n      <td>5.0</td>\n      <td>7</td>\n      <td>10</td>\n      <td>8</td>\n      <td>10</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>2015-01-08</th>\n      <td>9</td>\n      <td>12</td>\n      <td>13</td>\n      <td>6</td>\n      <td>7.0</td>\n      <td>8</td>\n      <td>6</td>\n      <td>12</td>\n      <td>11</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>2015-01-12</th>\n      <td>6</td>\n      <td>8</td>\n      <td>8</td>\n      <td>3</td>\n      <td>NaN</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n      <td>7</td>\n      <td>10</td>\n    </tr>\n    <tr>\n      <th>2015-01-13</th>\n      <td>9</td>\n      <td>11</td>\n      <td>13</td>\n      <td>6</td>\n      <td>8.0</td>\n      <td>7</td>\n      <td>6</td>\n      <td>9</td>\n      <td>8</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2015-01-14</th>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n      <td>9</td>\n      <td>4.0</td>\n      <td>7</td>\n      <td>8</td>\n      <td>5</td>\n      <td>3</td>\n      <td>10</td>\n    </tr>\n    <tr>\n      <th>2015-01-15</th>\n      <td>5</td>\n      <td>9</td>\n      <td>4</td>\n      <td>7</td>\n      <td>8.0</td>\n      <td>9</td>\n      <td>15</td>\n      <td>9</td>\n      <td>13</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2015-01-16</th>\n      <td>9</td>\n      <td>7</td>\n      <td>11</td>\n      <td>9</td>\n      <td>11.0</td>\n      <td>8</td>\n      <td>14</td>\n      <td>9</td>\n      <td>9</td>\n      <td>15</td>\n    </tr>\n    <tr>\n      <th>2015-01-17</th>\n      <td>10</td>\n      <td>8</td>\n      <td>10</td>\n      <td>6</td>\n      <td>14.0</td>\n      <td>13</td>\n      <td>16</td>\n      <td>9</td>\n      <td>4</td>\n      <td>14</td>\n    </tr>\n    <tr>\n      <th>2015-01-18</th>\n      <td>13</td>\n      <td>12</td>\n      <td>12</td>\n      <td>10</td>\n      <td>9.0</td>\n      <td>11</td>\n      <td>8</td>\n      <td>12</td>\n      <td>9</td>\n      <td>15</td>\n    </tr>\n    <tr>\n      <th>2015-01-19</th>\n      <td>4</td>\n      <td>8</td>\n      <td>12</td>\n      <td>11</td>\n      <td>9.0</td>\n      <td>7</td>\n      <td>10</td>\n      <td>6</td>\n      <td>11</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>2015-01-20</th>\n      <td>6</td>\n      <td>12</td>\n      <td>10</td>\n      <td>9</td>\n      <td>11.0</td>\n      <td>4</td>\n      <td>8</td>\n      <td>14</td>\n      <td>6</td>\n      <td>13</td>\n    </tr>\n    <tr>\n      <th>2015-01-21</th>\n      <td>9</td>\n      <td>15</td>\n      <td>4</td>\n      <td>12</td>\n      <td>7.0</td>\n      <td>9</td>\n      <td>1</td>\n      <td>5</td>\n      <td>12</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>2015-01-22</th>\n      <td>3</td>\n      <td>10</td>\n      <td>13</td>\n      <td>13</td>\n      <td>13.0</td>\n      <td>8</td>\n      <td>13</td>\n      <td>5</td>\n      <td>11</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>2015-01-23</th>\n      <td>8</td>\n      <td>7</td>\n      <td>9</td>\n      <td>20</td>\n      <td>5.0</td>\n      <td>12</td>\n      <td>8</td>\n      <td>7</td>\n      <td>8</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>2015-01-24</th>\n      <td>11</td>\n      <td>6</td>\n      <td>11</td>\n      <td>8</td>\n      <td>7.0</td>\n      <td>8</td>\n      <td>9</td>\n      <td>7</td>\n      <td>10</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2015-01-25</th>\n      <td>11</td>\n      <td>6</td>\n      <td>5</td>\n      <td>15</td>\n      <td>7.0</td>\n      <td>14</td>\n      <td>14</td>\n      <td>7</td>\n      <td>6</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>2015-01-26</th>\n      <td>4</td>\n      <td>7</td>\n      <td>10</td>\n      <td>7</td>\n      <td>6.0</td>\n      <td>10</td>\n      <td>9</td>\n      <td>12</td>\n      <td>7</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>2015-01-27</th>\n      <td>7</td>\n      <td>5</td>\n      <td>6</td>\n      <td>7</td>\n      <td>12.0</td>\n      <td>15</td>\n      <td>6</td>\n      <td>12</td>\n      <td>9</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>2015-01-28</th>\n      <td>8</td>\n      <td>8</td>\n      <td>12</td>\n      <td>14</td>\n      <td>8.0</td>\n      <td>11</td>\n      <td>7</td>\n      <td>12</td>\n      <td>10</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>2015-01-29</th>\n      <td>4</td>\n      <td>10</td>\n      <td>12</td>\n      <td>9</td>\n      <td>7.0</td>\n      <td>8</td>\n      <td>8</td>\n      <td>10</td>\n      <td>10</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>2015-01-30</th>\n      <td>6</td>\n      <td>7</td>\n      <td>7</td>\n      <td>11</td>\n      <td>7.0</td>\n      <td>7</td>\n      <td>9</td>\n      <td>16</td>\n      <td>10</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>2015-01-31</th>\n      <td>8</td>\n      <td>5</td>\n      <td>11</td>\n      <td>10</td>\n      <td>8.0</td>\n      <td>11</td>\n      <td>8</td>\n      <td>10</td>\n      <td>10</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2015-02-01</th>\n      <td>8</td>\n      <td>6</td>\n      <td>7</td>\n      <td>9</td>\n      <td>6.0</td>\n      <td>4</td>\n      <td>6</td>\n      <td>11</td>\n      <td>6</td>\n      <td>9</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('./data/catering_sale_all.xls', index_col='日期')\n",
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.925218Z",
     "end_time": "2024-05-23T11:29:08.323690Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "           百合酱蒸凤爪    翡翠蒸香茜饺   金银蒜汁蒸排骨     乐膳真味鸡     蜜汁焗餐包      生炒菜心    铁板酸菜豆腐  \\\n百合酱蒸凤爪   1.000000  0.009206  0.016799  0.455638  0.098085  0.308496  0.204898   \n翡翠蒸香茜饺   0.009206  1.000000  0.304434 -0.012279  0.058745 -0.180446 -0.026908   \n金银蒜汁蒸排骨  0.016799  0.304434  1.000000  0.035135  0.096218 -0.184290  0.187272   \n乐膳真味鸡    0.455638 -0.012279  0.035135  1.000000  0.016006  0.325462  0.297692   \n蜜汁焗餐包    0.098085  0.058745  0.096218  0.016006  1.000000  0.308454  0.502025   \n生炒菜心     0.308496 -0.180446 -0.184290  0.325462  0.308454  1.000000  0.369787   \n铁板酸菜豆腐   0.204898 -0.026908  0.187272  0.297692  0.502025  0.369787  1.000000   \n香煎韭菜饺    0.127448  0.062344  0.121543 -0.068866  0.155428  0.038233  0.095543   \n香煎罗卜糕   -0.090276  0.270276  0.077808 -0.030222  0.171005  0.049898  0.157958   \n原汁原味菜心   0.428316  0.020462  0.029074  0.421878  0.527844  0.122988  0.567332   \n\n            香煎韭菜饺     香煎罗卜糕    原汁原味菜心  \n百合酱蒸凤爪   0.127448 -0.090276  0.428316  \n翡翠蒸香茜饺   0.062344  0.270276  0.020462  \n金银蒜汁蒸排骨  0.121543  0.077808  0.029074  \n乐膳真味鸡   -0.068866 -0.030222  0.421878  \n蜜汁焗餐包    0.155428  0.171005  0.527844  \n生炒菜心     0.038233  0.049898  0.122988  \n铁板酸菜豆腐   0.095543  0.157958  0.567332  \n香煎韭菜饺    1.000000  0.178336  0.049689  \n香煎罗卜糕    0.178336  1.000000  0.088980  \n原汁原味菜心   0.049689  0.088980  1.000000  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>百合酱蒸凤爪</th>\n      <th>翡翠蒸香茜饺</th>\n      <th>金银蒜汁蒸排骨</th>\n      <th>乐膳真味鸡</th>\n      <th>蜜汁焗餐包</th>\n      <th>生炒菜心</th>\n      <th>铁板酸菜豆腐</th>\n      <th>香煎韭菜饺</th>\n      <th>香煎罗卜糕</th>\n      <th>原汁原味菜心</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>百合酱蒸凤爪</th>\n      <td>1.000000</td>\n      <td>0.009206</td>\n      <td>0.016799</td>\n      <td>0.455638</td>\n      <td>0.098085</td>\n      <td>0.308496</td>\n      <td>0.204898</td>\n      <td>0.127448</td>\n      <td>-0.090276</td>\n      <td>0.428316</td>\n    </tr>\n    <tr>\n      <th>翡翠蒸香茜饺</th>\n      <td>0.009206</td>\n      <td>1.000000</td>\n      <td>0.304434</td>\n      <td>-0.012279</td>\n      <td>0.058745</td>\n      <td>-0.180446</td>\n      <td>-0.026908</td>\n      <td>0.062344</td>\n      <td>0.270276</td>\n      <td>0.020462</td>\n    </tr>\n    <tr>\n      <th>金银蒜汁蒸排骨</th>\n      <td>0.016799</td>\n      <td>0.304434</td>\n      <td>1.000000</td>\n      <td>0.035135</td>\n      <td>0.096218</td>\n      <td>-0.184290</td>\n      <td>0.187272</td>\n      <td>0.121543</td>\n      <td>0.077808</td>\n      <td>0.029074</td>\n    </tr>\n    <tr>\n      <th>乐膳真味鸡</th>\n      <td>0.455638</td>\n      <td>-0.012279</td>\n      <td>0.035135</td>\n      <td>1.000000</td>\n      <td>0.016006</td>\n      <td>0.325462</td>\n      <td>0.297692</td>\n      <td>-0.068866</td>\n      <td>-0.030222</td>\n      <td>0.421878</td>\n    </tr>\n    <tr>\n      <th>蜜汁焗餐包</th>\n      <td>0.098085</td>\n      <td>0.058745</td>\n      <td>0.096218</td>\n      <td>0.016006</td>\n      <td>1.000000</td>\n      <td>0.308454</td>\n      <td>0.502025</td>\n      <td>0.155428</td>\n      <td>0.171005</td>\n      <td>0.527844</td>\n    </tr>\n    <tr>\n      <th>生炒菜心</th>\n      <td>0.308496</td>\n      <td>-0.180446</td>\n      <td>-0.184290</td>\n      <td>0.325462</td>\n      <td>0.308454</td>\n      <td>1.000000</td>\n      <td>0.369787</td>\n      <td>0.038233</td>\n      <td>0.049898</td>\n      <td>0.122988</td>\n    </tr>\n    <tr>\n      <th>铁板酸菜豆腐</th>\n      <td>0.204898</td>\n      <td>-0.026908</td>\n      <td>0.187272</td>\n      <td>0.297692</td>\n      <td>0.502025</td>\n      <td>0.369787</td>\n      <td>1.000000</td>\n      <td>0.095543</td>\n      <td>0.157958</td>\n      <td>0.567332</td>\n    </tr>\n    <tr>\n      <th>香煎韭菜饺</th>\n      <td>0.127448</td>\n      <td>0.062344</td>\n      <td>0.121543</td>\n      <td>-0.068866</td>\n      <td>0.155428</td>\n      <td>0.038233</td>\n      <td>0.095543</td>\n      <td>1.000000</td>\n      <td>0.178336</td>\n      <td>0.049689</td>\n    </tr>\n    <tr>\n      <th>香煎罗卜糕</th>\n      <td>-0.090276</td>\n      <td>0.270276</td>\n      <td>0.077808</td>\n      <td>-0.030222</td>\n      <td>0.171005</td>\n      <td>0.049898</td>\n      <td>0.157958</td>\n      <td>0.178336</td>\n      <td>1.000000</td>\n      <td>0.088980</td>\n    </tr>\n    <tr>\n      <th>原汁原味菜心</th>\n      <td>0.428316</td>\n      <td>0.020462</td>\n      <td>0.029074</td>\n      <td>0.421878</td>\n      <td>0.527844</td>\n      <td>0.122988</td>\n      <td>0.567332</td>\n      <td>0.049689</td>\n      <td>0.088980</td>\n      <td>1.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.944760Z",
     "end_time": "2024-05-23T11:29:08.324690Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "百合酱蒸凤爪     1.000000\n翡翠蒸香茜饺     0.009206\n金银蒜汁蒸排骨    0.016799\n乐膳真味鸡      0.455638\n蜜汁焗餐包      0.098085\n生炒菜心       0.308496\n铁板酸菜豆腐     0.204898\n香煎韭菜饺      0.127448\n香煎罗卜糕     -0.090276\n原汁原味菜心     0.428316\nName: 百合酱蒸凤爪, dtype: float64"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr()['百合酱蒸凤爪']"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.959217Z",
     "end_time": "2024-05-23T11:29:08.325690Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [
    {
     "data": {
      "text/plain": "0.009205803051836475"
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['百合酱蒸凤爪'].corr(data['翡翠蒸香茜饺'])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.967846Z",
     "end_time": "2024-05-23T11:29:08.325690Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 3.3 Python主要数据探索函数\n",
    "#### 3.3.1 基本统计特征函数"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "data": {
      "text/plain": "   0  1  2  3  4  5  6\n0  1  2  3  4  5  6  7\n1  2  3  4  5  6  7  8",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>6</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D = pd.DataFrame([range(1, 8), range(2, 9)])\n",
    "D"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.974135Z",
     "end_time": "2024-05-23T11:29:08.397758Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [
    {
     "data": {
      "text/plain": "     0    1    2    3    4    5    6\n0  1.0  1.0  1.0  1.0  1.0  1.0  1.0\n1  1.0  1.0  1.0  1.0  1.0  1.0  1.0\n2  1.0  1.0  1.0  1.0  1.0  1.0  1.0\n3  1.0  1.0  1.0  1.0  1.0  1.0  1.0\n4  1.0  1.0  1.0  1.0  1.0  1.0  1.0\n5  1.0  1.0  1.0  1.0  1.0  1.0  1.0\n6  1.0  1.0  1.0  1.0  1.0  1.0  1.0",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.corr(method='spearman')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.984499Z",
     "end_time": "2024-05-23T11:29:08.438780Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "outputs": [
    {
     "data": {
      "text/plain": "1.0"
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S1 = D.loc[0]\n",
    "S2 = D.loc[1]\n",
    "S1.corr(S2, method='pearson')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:07.999033Z",
     "end_time": "2024-05-23T11:29:08.463772Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [
    {
     "data": {
      "text/plain": "          0         1         2         3         4\n0  0.816240  1.336056  1.614377 -0.655009 -1.701274\n1  0.559116  1.802305 -1.013297 -0.936503  0.439421\n2  0.596408 -1.485477  1.460830  0.219149  0.070956\n3 -1.045856 -1.345525 -0.179871  0.693808  0.883413\n4  0.064879  0.274011  0.408451  1.791892 -0.212301\n5 -0.461930 -0.223318 -0.167939 -0.999390  0.047768",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.816240</td>\n      <td>1.336056</td>\n      <td>1.614377</td>\n      <td>-0.655009</td>\n      <td>-1.701274</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.559116</td>\n      <td>1.802305</td>\n      <td>-1.013297</td>\n      <td>-0.936503</td>\n      <td>0.439421</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.596408</td>\n      <td>-1.485477</td>\n      <td>1.460830</td>\n      <td>0.219149</td>\n      <td>0.070956</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-1.045856</td>\n      <td>-1.345525</td>\n      <td>-0.179871</td>\n      <td>0.693808</td>\n      <td>0.883413</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.064879</td>\n      <td>0.274011</td>\n      <td>0.408451</td>\n      <td>1.791892</td>\n      <td>-0.212301</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>-0.461930</td>\n      <td>-0.223318</td>\n      <td>-0.167939</td>\n      <td>-0.999390</td>\n      <td>0.047768</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D = pd.DataFrame(np.random.randn(6, 5))\n",
    "D"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.013673Z",
     "end_time": "2024-05-23T11:29:08.464773Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "outputs": [
    {
     "data": {
      "text/plain": "          0         1         2         3         4\n0  0.519870  0.541778  0.345505 -0.217064 -0.403760\n1  0.541778  1.830802 -0.314924 -0.622938 -0.563151\n2  0.345505 -0.314924  1.048705  0.189259 -0.634953\n3 -0.217064 -0.622938  0.189259  1.208593  0.182421\n4 -0.403760 -0.563151 -0.634953  0.182421  0.776619",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.519870</td>\n      <td>0.541778</td>\n      <td>0.345505</td>\n      <td>-0.217064</td>\n      <td>-0.403760</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.541778</td>\n      <td>1.830802</td>\n      <td>-0.314924</td>\n      <td>-0.622938</td>\n      <td>-0.563151</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.345505</td>\n      <td>-0.314924</td>\n      <td>1.048705</td>\n      <td>0.189259</td>\n      <td>-0.634953</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-0.217064</td>\n      <td>-0.622938</td>\n      <td>0.189259</td>\n      <td>1.208593</td>\n      <td>0.182421</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>-0.403760</td>\n      <td>-0.563151</td>\n      <td>-0.634953</td>\n      <td>0.182421</td>\n      <td>0.776619</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.cov()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.021163Z",
     "end_time": "2024-05-23T11:29:08.464773Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "outputs": [
    {
     "data": {
      "text/plain": "0.5417780900407864"
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D[0].cov(D[1])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.031374Z",
     "end_time": "2024-05-23T11:29:08.465773Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "outputs": [
    {
     "data": {
      "text/plain": "0   -0.802726\n1    0.108364\n2    0.142904\n3    0.824844\n4   -1.419999\ndtype: float64"
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.skew()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.039660Z",
     "end_time": "2024-05-23T11:29:08.507827Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "outputs": [
    {
     "data": {
      "text/plain": "0   -0.701581\n1   -1.763336\n2   -1.364769\n3   -0.401561\n4    2.874308\ndtype: float64"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.kurt()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.049626Z",
     "end_time": "2024-05-23T11:29:08.508833Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "outputs": [
    {
     "data": {
      "text/plain": "              0         1         2         3         4\ncount  6.000000  6.000000  6.000000  6.000000  6.000000\nmean   0.088143  0.059675  0.353759  0.018991 -0.078670\nstd    0.721020  1.353071  1.024063  1.099360  0.881260\nmin   -1.045856 -1.485477 -1.013297 -0.999390 -1.701274\n25%   -0.330228 -1.064973 -0.176888 -0.866129 -0.147284\n50%    0.311998  0.025347  0.120256 -0.217930  0.059362\n75%    0.587085  1.070544  1.197735  0.575144  0.347305\nmax    0.816240  1.802305  1.614377  1.791892  0.883413",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>6.000000</td>\n      <td>6.000000</td>\n      <td>6.000000</td>\n      <td>6.000000</td>\n      <td>6.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>0.088143</td>\n      <td>0.059675</td>\n      <td>0.353759</td>\n      <td>0.018991</td>\n      <td>-0.078670</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>0.721020</td>\n      <td>1.353071</td>\n      <td>1.024063</td>\n      <td>1.099360</td>\n      <td>0.881260</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>-1.045856</td>\n      <td>-1.485477</td>\n      <td>-1.013297</td>\n      <td>-0.999390</td>\n      <td>-1.701274</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>-0.330228</td>\n      <td>-1.064973</td>\n      <td>-0.176888</td>\n      <td>-0.866129</td>\n      <td>-0.147284</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>0.311998</td>\n      <td>0.025347</td>\n      <td>0.120256</td>\n      <td>-0.217930</td>\n      <td>0.059362</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>0.587085</td>\n      <td>1.070544</td>\n      <td>1.197735</td>\n      <td>0.575144</td>\n      <td>0.347305</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>0.816240</td>\n      <td>1.802305</td>\n      <td>1.614377</td>\n      <td>1.791892</td>\n      <td>0.883413</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.describe()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.058569Z",
     "end_time": "2024-05-23T11:29:08.526829Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.3.2 拓展统计特征函数"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "outputs": [
    {
     "data": {
      "text/plain": "0       0\n1       1\n2       3\n3       6\n4      10\n5      15\n6      21\n7      28\n8      36\n9      45\n10     55\n11     66\n12     78\n13     91\n14    105\n15    120\n16    136\n17    153\n18    171\n19    190\ndtype: int64"
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D = pd.Series(range(0, 20))\n",
    "D.cumsum()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.078419Z",
     "end_time": "2024-05-23T11:29:08.526829Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "outputs": [
    {
     "data": {
      "text/plain": "0      NaN\n1      1.0\n2      3.0\n3      5.0\n4      7.0\n5      9.0\n6     11.0\n7     13.0\n8     15.0\n9     17.0\n10    19.0\n11    21.0\n12    23.0\n13    25.0\n14    27.0\n15    29.0\n16    31.0\n17    33.0\n18    35.0\n19    37.0\ndtype: float64"
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.rolling(2).sum()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.087843Z",
     "end_time": "2024-05-23T11:29:08.527828Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "#### 3.3.3 统计绘图函数"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 50)\n",
    "y = np.sin(x)\n",
    "plt.plot(x, y, 'bp--')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.098692Z",
     "end_time": "2024-05-23T11:29:08.637853Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'\n",
    "sizes = [15, 30, 45, 10]\n",
    "colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']\n",
    "explode = (0, 0.1, 0, 0)\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.0f%%', shadow=True, startangle=90)\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.208463Z",
     "end_time": "2024-05-23T11:29:08.902918Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.randn(1000)\n",
    "plt.hist(x, 10)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.296686Z",
     "end_time": "2024-05-23T11:29:08.967929Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = pd.DataFrame([x, x + 1]).T\n",
    "D.plot(kind='box')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.400759Z",
     "end_time": "2024-05-23T11:29:08.968930Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x900 with 2 Axes>",
      "image/png": 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7dyc/P981yAkgPz+fCRMmsGLFCiIjI3n44YdrHUprM0+pO9m1axd9+/attu77779n165dXHPNNYSHh5+2j2EYp3XXFxcX4+vre9bu84qKCp599lmuv/56evTo4Vq/YMECLrvsMnr16uVa98UXXzBgwABat2591rorKipwOBxYrdYafU93/jMSERFxJ29uSuepz1L4Xc82vHZ7/0b97JrOU1qnUNpUeGoobS70ZyQiItI4Hv1kN+9uOcTk4V2ZceUFjfrZNQ2lTW/mVBERERGpV645SpvqdFAolIqIiIh4NMMw2JddCEC3yKY58h6aQSh147sTPN4vn0glIiIiDeN4cRn5JeVYLNA1oumG0to/kN1N+Pr6YrFYyMnJISIi4qxzdkrjMwyDsrIycnJy8PLy0jymIiIiDahq5H1UaCABfk1z5D14cCj19vamY8eOHDlyhIyMDLPLkTMIDAykU6dOeHl5fIO9iIiIadJOdd3HNuGue/DgUArQsmVLYmNjzzmHqpjD29sbHx8ftWCLiIg0sKonOXVrok9yquLRoRQqw4+3d9NtqhYRERFpSKluMPIemsFAJxEREZHmzPXM+ybefa9QKiIiIuKh8orLyC2qfNx3V4VSERERETFDWk5lK2n7YH9aWpv2XZsKpSIiIiIequp+0m5tmvb9pKBQKiIiIuKxUt1kOihQKBURERHxWGluMsgJFEpFREREPJZrOqgmPkcpKJSKiIiIeKTC0nKybKUAdIvQPaUiIiIiYoKqrvvIVlaCA31Nrub8FEpFREREPJBr0nw36LoHhVIRERERj/TzIKem33UPCqUiIiIiHin1WOV0UN3cYOQ9KJSKiIiIeCR3eeZ9FYVSEREREQ9TUlbBkbyTAMS6wdOcQKFURERExOPszy4GILyFH2Et/EyupmYUSkVEREQ8TNXjRd3lflJQKBURERHxOO42HRQolIqIiIh4HNfjRd1kOihQKBURERHxOGmnuu/dZeQ9KJSKiIiIeJTScgeHTpQA0E3d9yIiIiJihgM5xTgNCA7wJaKl1exyakyhVERERMSDpP6i695isZhcTc0plIqIiIh4kDQ3HHkPdQilubm5xMTEkJGRUaPtx4wZg8Vicb0SExNd73399df06NGD1q1bM2fOnNqWIiIiIiK/UjXyvpsbjbyHWobS3NxcRo0aVeNACrBt2zZ2795NXl4eeXl5LF26FICcnBzGjBnDuHHjSEpK4p133mHt2rW1Kl5EREREqkt1w5H3UMtQOnbsWMaPH1/j7TMzMzEMgwsvvJCQkBBCQkJo0aIFAO+88w7t27fn8ccfJzY2lieeeIKFCxee83h2ux2bzVbtJSIiIiKVyiqcZByvHHnv0d33CxYsYMqUKTXefuvWrTgcDjp27EiLFi0YO3YseXl5AOzatYvhw4e7bsAdMGAA27dvP+fxZs+eTXBwsOsVFRVVm/JFREREPFrG8WIcToOWVh/aBvmbXU6t1CqUxsTE1Orge/bsoW/fvnz++eds3ryZ9PR0Zs6cCYDNZqt2vKCgII4ePXrO482cOZOCggLX6/Dhw7WqR0RERMSTVd1P2tXNRt5DA4++nzlzJitXrqRv37707t2bf/zjHyxZsgQAHx8frNaf587y9/enpKTknMezWq0EBQVVe4mIiIhIJXe9nxQaeUqoyMhIjh8/jt1uJywsjJycHNd7hYWF+Pn5NWY5IiIiIh7FNR2UQml1t9xyCxs3bnQtJyUl0aZNG6xWK/Hx8SQlJbne27FjBx06dGjIckREREQ8mrvOUQr1FEptNhvl5eWnre/duzfTpk1j48aNfPrpp8ycOZNJkyYBlfOXbtq0iVWrVlFeXs6zzz7LlVdeWR/liIiIiDQ7FQ4nB3KKAYh1szlKAXzq4yB9+vRh3rx5XHfdddXWP/zww6Snp3PVVVfRqlUr7rvvPh599FEAWrduzdy5c7nmmmto2bIlISEhLFq0qD7KEREREWl2Dp0ooczhxN/Xiw4hAWaXU2sWwzAMMwtIT09nz549DB48mJYta9fUbLPZCA4OpqCgQIOeREREpFlb8UMW9yzezoUdgvjvA4PNLselpnmtXlpKf4uYmJhaTzUlIiIiItX9PMjJ/bruoZFH34uIiIhIw0g9VjkdVDc3HHkPCqUiIiIiHiHVjaeDAoVSEREREbfncBq/mA5K3fciIiIiYoLMvJPYK5z4+XgRFep+I+9BoVRERETE7VU9XrRL6xb4eLtnvHPPqkVERETEJdXNu+5BoVRERETE7aUec+9BTqBQKiIiIuL20k513yuUioiIiIgpDMP4Rfe9QqmIiIiImOBoQSklZQ58vCx0Dm9hdjl1plAqIiIi4saqnuQU07oFvm468h4USkVERETcWpoHdN2DQqmIiIiIW6saed8t0n2ngwKFUhERERG3luoBI+9BoVRERETEbf1y5H03hVIRERERMUN2oZ3C0gq8LJUDndyZQqmIiIiIm6oa5NQ5vAX+vt4mV/PbKJSKiIiIuKmq6aDcveseFEpFRERE3JbrSU4KpSIiIiJiFk94vGgVhVIRERERN+WaON/N5ygFhVIRERERt3S8yM6J4jIsFugaoZZSERERETFBVdd9x9AAAvzce+Q9KJSKiIiIuKVUD+q6B4VSEREREbeUdswzHi9aRaFURERExA15yuNFqyiUioiIiLihn6eDaqbd97m5ucTExJCRkVGj7V977TXatWuHr68vQ4cO5aeffnK9N2bMGCwWi+uVmJhY23JEREREmp38kjJyCu1AM20pzc3NZdSoUTUOpBs3buTxxx9n8eLFpKenYxgGf/zjH13vb9u2jd27d5OXl0deXh5Lly6tVfEiIiIizVHV/KTtg/1pafUxuZr6UatQOnbsWMaPH1/j7VNTU/nXv/5FYmIiHTt2ZMKECezYsQOAzMxMDMPgwgsvJCQkhJCQEFq0aFG76kVERESaIdf9pB7SdQ+1DKULFixgypQpNd5+woQJXHfdda7lvXv3EhsbC8DWrVtxOBx07NiRFi1aMHbsWPLy8s55PLvdjs1mq/YSERERaW5Sj3nOM++r1CqUxsTE1PmDTpw4wb/+9S/uvfdeAPbs2UPfvn35/PPP2bx5M+np6cycOfOcx5g9ezbBwcGuV1RUVJ3rEREREXFXqdmeNR0UgMUwDKPWO1kspKenEx0dXeN9xo0bh81m4/PPPz/j++vXr+eGG24gNzf3rMew2+3Y7XbXss1mIyoqioKCAoKCgmpci4iIiIg7Gzh7NT8VlPKfSQPp1znM7HLOyWazERwcfN681ih3xr711lusXbuWXbt2nXWbyMhIjh8/jt1ux2q1nnEbq9V61vdEREREmoPC0nJ+KigFoFtEM72ntC62bdvGAw88wPvvv0+bNm1c62+55RY2btzoWk5KSqJNmzYKnSIiIiLnUDXyPrKVleBAX5OrqT/1EkptNhvl5eWnrc/Ozmb06NH86U9/on///hQVFVFUVHkie/fuzbRp09i4cSOffvopM2fOZNKkSfVRjoiIiIjH+nnSfM+5nxTqKZT26dPnjPeKvvfee2RlZfH444/TqlUr1wvg4Ycfpk+fPlx11VVMmjSJ++67jz//+c/1UY6IiIiIx6pqKY2N9Jyue6jjQKemoqY3zoqIiIh4ij8s+pY1e7J5+roL+X1CZ7PLOa+a5rUGv6dUREREROqPJ04HBQqlIiIiIm6jpKyCI3knAYVSERERETHJgZxiDAPCWvgR3tKzZixSKBURERFxE1Vd9908rJUUFEpFRERE3IYnPvO+ikKpiIiIiJtwzVGqUCoiIiIiZnHNUdrGs+YoBYVSEREREbdQWu7g4PFiQC2lIiIiImKS9NxinAYE+fsQ0cqzRt6DQqmIiIiIW0j9Rde9xWIxuZr6p1AqIiIi4gbSjnnmk5yqKJSKiIiIuIGqllJPnKMUFEpFRERE3EKqB4+8B4VSERERkSavrMJJRq7njrwHhVIRERGRJu/g8WIqnAYt/LxpF+xvdjkNQqFUREREpIlz3U/qoSPvQaFUREREpMnz5GfeV1EoFREREWniUrM9ezooUCgVERERafJ+fua9QqmIiIiImKDC4eRATtXIe8+cDgoUSkVERESatEMnSihzOPH39aJDSIDZ5TQYhVIRERGRJiztF09y8vLyzJH3oFAqIiIi0qS5nuTkwV33oFAqIiIi0qSlefgz76solIqIiIg0YVXTQSmUioiIiIgpnE7j5+mgFEpFRERExAyZ+ScpLXfi5+1Fp7BAs8tpUAqlIiIiIk1UVdd9l4gW+Hh7dmzz7G8nIiIi4saqnnnv6feTgkKpiIiISJPVXKaDgjqE0tzcXGJiYsjIyKjR9l9//TU9evSgdevWzJkzp9p7S5YsoXPnzrRv35733nuvtqWIiIiIeLTUZvDM+yq1CqW5ubmMGjWqxoE0JyeHMWPGMG7cOJKSknjnnXdYu3YtAMnJydx66608/vjjrFixgieeeIK9e/fW+guIiIiIeCLDMEg7VnlPqaePvIdahtKxY8cyfvz4Gm//zjvv0L59ex5//HFiY2N54oknWLhwIQCvv/46w4cPZ+LEifTu3Zv777+fxYsX1656EREREQ/1U0EpxWUOfLwsdA5vYXY5Da5WoXTBggVMmTKlxtvv2rWL4cOHY7FUPqd1wIABbN++3fXeiBEjXNv+8r2zsdvt2Gy2ai8RERERT1TVdR/dugV+Pp4/DKhW3zAmJqZWB7fZbNX2CQoK4ujRo+d972xmz55NcHCw6xUVFVWrekRERETcRWoz6rqHBh597+Pjg9VqdS37+/tTUlJy3vfOZubMmRQUFLhehw8fbpjCRUREREzWXJ7kVMWnIQ8eFhZGTk6Oa7mwsBA/P7/zvnc2Vqu1WpAVERER8VRV3ffd2nj+dFDQwC2l8fHxJCUluZZ37NhBhw4dzvueiIiISHNmGIa67+vCZrNRXl5+2voxY8awadMmVq1aRXl5Oc8++yxXXnklADfeeCPvv/8+u3fvpqioiBdeeMH1noiIiEhzllNox1ZagZcFYlp7/sh7qKdQ2qdPHz7//PPT1rdu3Zq5c+dyzTXX0KZNG/bu3ctjjz0GQN++fZk6dSr9+/enQ4cOeHt7c99999VHOSIiIiJurarrvnN4C/x9vU2upnFYDMMwGvpD0tPT2bNnD4MHD6Zly+pN0CkpKWRmZjJ06NDz3lP6azabjeDgYAoKCggKCqrPkkVERERMs2hTOk9+lsLInm1YcHt/s8v5TWqa1xp0oFOVmJiYs04n1bNnT3r27NkYZYiIiIi4hdRmNvIeGnigk4iIiIjUXnN65n0VhVIRERGRJma/q6W0eUwHBQqlIiIiIk3K8SI7x4vLsFiga4RaSkVERETEBFVPcuoYGkCAX/MYeQ8KpSIiIiJNiutJTs2olRQUSkVERESaFNcz75vJ40WrKJSKiIiINCGp2ZWPF+3WjKaDAoVSERERkSYl9Vjzm6MUFEpFREREmoyCknKyC+2AWkpFRERExCRpOZVd9+2C/Wnl72tyNY1LoVRERESkiajqum9uraSgUCoiIiLSZKQ2wyc5VVEoFREREWkimuMz76solIqIiIg0EWnHKu8pbW4j70GhVERERKRJKCwt52hBKaB7SkVERETEJPtzigGIaGUlJNDP5Goan0KpiIiISBOQ2oy77kGhVERERKRJcD3zXqFURERERMxSNfK+W5vmNx0UKJSKiIiINAmp2eq+FxERERETlZRVcCTvJKBQKiIiIiImOZBTjGFAWAs/wltazS7HFAqlIiIiIiarGuTUHOcnraJQKiIiImKy5n4/KSiUioiIiJgu9Vjzng4KFEpFRERETOeao7SZTgcFCqUiIiIiprJXOMg4XvmIUbWUioiIiIgp0nOLcRrQyt+HiFbNc+Q91CGUJicnEx8fT2hoKDNmzMAwjHNuf+edd2KxWE57ZWRkYBgGISEh1db/7W9/q/OXEREREXE3v7yf1GKxmFyNeWoVSu12O6NHj6Zfv35s27aNlJQUFi1adM59Xn75ZfLy8lyvL774gtjYWKKiokhNTSUkJKTa+zNmzPgt30dERETEraS6nnnffO8nhVqG0uXLl1NQUMCcOXPo2rUrs2bNYuHChefcJzAwkJCQENdr7ty5PPnkk3h7e/Ptt98ycODAau9brc232VpERESan7Sq6aDaNN/7SaGWoXTXrl0kJCQQGBgIQJ8+fUhJSanx/t9++y3p6emMHTsWgK1bt7J161ZCQkKIjIzkscceO+ftAHa7HZvNVu0lIiIi4s6quu+b88T5UMtQarPZiImJcS1bLBa8vb3Jy8ur0f4vvvgikyZNwsur8mP37dvH6NGj2bFjB++++y6vvvoqH3zwwVn3nz17NsHBwa5XVFRUbcoXERERaVLKHU7Sc0+NvG/G00FBLUOpj4/Pad3r/v7+lJSUnHffEydOsHTpUiZMmOBat3z5cubNm0dMTAyJiYlMmTKFJUuWnPUYM2fOpKCgwPU6fPhwbcoXERERaVIOHi+mwmnQws+b9sH+ZpdjKp/abBwWFkZycnK1dYWFhfj5+Z13348//pjBgwcTGhp61m0iIyPJzMw86/tWq1X3nIqIiIjH+GXXfXMeeQ+1bCmNj48nKSnJtZyeno7dbicsLOy8+3744YfccMMNruWTJ0/Su3dvTp486VqXlJRE586da1OSiIiIiNuqGnnfrZmPvIdahtIhQ4Zgs9l48803AZg1axaJiYl4e3uTn5+Pw+E4434nT57k66+/ZtiwYa51AQEBtGnThvvuu49t27Yxd+5c3n33XSZNmlT3byMiIiLiRlzTQTXzkfdQy+57Hx8fXn/9dcaNG8eMGTPw8vJi3bp1AISGhrJjxw4uuuii0/b75ptvCA0NpUuXLtXWv/HGG9x5550MGjSI6Oho3n//fYYOHVrnLyMiIiLiTlKPnZoOqpmPvAewGOd7JNMZZGVlsX37dhISEggPD2+IumrEZrMRHBxMQUEBQUFBptUhIiIiUlsVDic9/7KCsgon62cMp1N4oNklNYia5rVatZRWadu2Lddee22dixMRERFp7g7nnaSswom/rxcdQgPMLsd0tbqnVERERETqR1XXfdeIlnh7Ne+R96BQKiIiImKKn595r/tJQaFURERExBRprpH3mg4KFEpFRERETJGaXdl939yfeV9FoVRERESkkTmdBvuzTz3zXqEUUCgVERERaXSZ+Sc5We7Az9uLTmGeORVUbSmUioiIiDSybQdPANAlogU+3opjoFAqIiIi0qgMw+DNTRkAXHVhW3OLaUIUSkVEREQa0baDeXx/pAA/Hy9+n9DZ7HKaDIVSERERkUb0+oYDANx4SQfCW1pNrqbpUCgVERERaSQHjxfzVcoxAP5weYzJ1TQtCqUiIiIijeTNTRkYBgzrHqFJ839FoVRERESkERSUlPPhtsMATBzUxeRqmh6FUhEREZFG8N63hygpc3BB21Zc3i3c7HKaHIVSERERkQZW7nCy6NQ0UP87KAaLxWJuQU2QQqmIiIhIA/ti909k2Upp3dLKmIvam11Ok6RQKiIiItKADMNgwalpoO4Y2Bmrj7fJFTVNCqUiIiIiDWhr+gmSM21Yfby4VZPln5VCqYiIiEgDen1jOgA39utIWAs/k6tpuhRKRURERBpIem4xq37UZPk1oVAqIiIi0kDe3JSOYcCICyLpFtnS7HKaNIVSERERkQaQX1LGR9uOADBxkFpJz0ehVERERKQBvLv1ECfLHfRoF8TArpos/3wUSkVERETqWVmFk7e+yQAqW0k1Wf75KZSKiIiI1LPPdx/lmM1OZCsro/tqsvyaUCgVERERqUeGYfD6hsppoO64LBo/H8WtmtBZEhEREalHmw+c4IejNvx9vRg/oJPZ5bgNhVIRERGRevT6qUeK/r9+HQnVZPk1VutQmpycTHx8PKGhocyYMQPDMM67T58+fbBYLK7XxIkTXe8tWbKEzp070759e957773aliMiIiLSZOzPKWL1nmwsFk2WX1u1CqV2u53Ro0fTr18/tm3bRkpKCosWLTrnPiUlJezfv5/s7Gzy8vLIy8vjxRdfBCoD7q233srjjz/OihUreOKJJ9i7d2+dv4yIiIiImd449UjRKy5oQ5cITZZfG7UKpcuXL6egoIA5c+bQtWtXZs2axcKFC8+5z44dO+jTpw8RERGEhIQQEhJCQEAAAK+//jrDhw9n4sSJ9O7dm/vvv5/FixfX/duIiIiImOREcRn/+e7UZPmD1UpaW7UKpbt27SIhIYHAwECgsls+JSXlnPts3bqVI0eOuELppEmTsNvtruONGDHCte2AAQPYvn37WY9lt9ux2WzVXiIiIiJNwbtbDlJa7uTCDkFcGhNmdjlup1ah1GazERPzc/K3WCx4e3uTl5d31n327t3LoEGD2LhxIytWrGDlypXMnTv3jMcLCgri6NGjZz3W7NmzCQ4Odr2ioqJqU76IiIhIg7BXOHgr6SAAEwd10WT5dVCrUOrj44PVaq22zt/fn5KSkrPu8+qrr/Lee+/RvXt3Lr30Up544gmWLFlyxuOd71gzZ86koKDA9Tp8+HBtyhcRERFpEJ/t+omcQjttg/y5pnc7s8txSz612TgsLIzk5ORq6woLC/Hzq/l0B5GRkWRmZrqOl5OTU+NjWa3W00KxiIiIiJkqJ8uvnAZKk+XXXa3OWnx8PElJSa7l9PR07HY7YWFnv29i4MCB1Vo0k5KS6Ny58xmPt2PHDjp06FCbkkRERERM9c3+4+zJKiTA11uT5f8GtQqlQ4YMwWaz8eabbwIwa9YsEhMT8fb2Jj8/H4fDcdo+vXr14p577mHLli289dZbPPfcc0yaNAmAG2+8kffff5/du3dTVFTECy+8wJVXXlkPX0tERESkcVS1kt7cvyPBgb4mV+O+LEZNZr//hWXLljFu3DgCAgLw8vJi3bp19OzZE4vFwo4dO7jooouqbZ+fn8+ECRNYsWIFkZGRPPzww65QCvDnP/+Zf/7zn/j7+xMbG8uGDRtcU0adj81mIzg4mIKCAoKCgmrzNURERER+s7TsQhLnrMdigbXThxHduoXZJTU5Nc1rtQ6lAFlZWWzfvp2EhATCw8N/U6EAKSkpZGZmMnTo0Frdn6pQKiIiImaa+fFu3tt6iN/1bMNrt/c3u5wmqaZ5rVYDnaq0bduWa6+9ts7F/VrPnj3p2bNnvR1PREREpKEdL7LzsWuy/C4mV+P+NDxMREREpA7e2XIIe4WTPh2DiY8ONbsct6dQKiIiIlJLpeUO/p2UAcD/DorRZPn1QKFUREREpJaW7TpKblEZ7YI1WX59USgVERERqQXDMFi4IR2AOy+Lxtdbcao+6CyKiIiI1MLGtFz2Hisk0M+bsZosv94olIqIiIjUwuunWklv7h9FcIAmy68vCqUiIiIiNbTvWCFf78vBYoE/XB5jdjkeRaFUREREpIbe2FjZSnplz7Z0Cg80uRrPolAqIiIiUgO5RXY+3pEJwF1D1Epa3xRKRURERGrg7c0HKatwclFUCJd00mT59U2hVEREROQ8SssdLE46CMDEwZosvyEolIqIiIicx9KdmRwvLqNDSABX9WprdjkeSaFURERE5BwMw3BNAzXh8mh8NFl+g9BZFRERETmH9am5pGYX0dLqw83xUWaX47EUSkVERETO4fUNBwC4JT6KIH9Nlt9QFEpFREREzmJvViEbUnPxslQ+514ajkKpiIiIyFks3FjZSnr1he2ICtNk+Q1JoVRERETkDHIK7Xy64ygA/ztYk+U3NIVSERERkTNYvPkgZQ4nl3TSZPmNQaFURERE5FdKyx28vblqsvwuJlfTPCiUioiIiPzKJzsyOVFcRsfQAH7Xs43Z5TQLCqUiIiIiv+B0Gq5poCZcHqPJ8huJzrKIiIjIL3y9L4f9OcW0svpwc/+OZpfTbCiUioiIiPzC66emgRo7IIpWmiy/0SiUioiIiJySctTGprTjeHtZuEOT5TcqhVIRERGRUxZuTAfg6gvb0jFUk+U3JoVSERERESDbVsqyXZmApoEyg0KpiIiICPDvpIOUOwz6dw7loqgQs8tpdmodSpOTk4mPjyc0NJQZM2ZgGMZ593nqqacICwvDarVy/fXXU1hY6HqvT58+WCwW12vixIm1LUlERETkNzlZ5uDtLZos30y1CqV2u53Ro0fTr18/tm3bRkpKCosWLTrnPu+88w7vvPMOX375JT/88AM//vgj//d//wdASUkJ+/fvJzs7m7y8PPLy8njxxRfr/GVERERE6uI/3x0hv6ScTmGBjNRk+aaoVShdvnw5BQUFzJkzh65duzJr1iwWLlx4zn0OHz7MW2+9xYABA+jWrRu33HILO3bsAGDHjh306dOHiIgIQkJCCAkJISAgoO7fRkRERKSWnE6DN04NcPrD5dF4e1lMrqh58qnNxrt27SIhIYHAwMrRaH369CElJeWc+zzyyCPVlvfu3UtsbCwAW7du5ciRI0RERFBeXs64ceOYN28eVqv1jMey2+3Y7XbXss1mq035IiIiIqdZuzebA7nFtPL34ab+UWaX02zVqqXUZrMRExPjWrZYLHh7e5OXl1ej/fft28cnn3zC3XffDVQG1EGDBrFx40ZWrFjBypUrmTt37ln3nz17NsHBwa5XVJR+cERERKTuTpY5eHFNGgDjL+1EC2ut2uukHtUqlPr4+JzWiunv709JScl593U6nfzhD39g4sSJ9OrVC4BXX32V9957j+7du3PppZfyxBNPsGTJkrMeY+bMmRQUFLhehw8frk35IiIiIi4/FZzkpn99w87D+fj7enHHwGizS2rWavXfgbCwMJKTk6utKywsxM/P77z7Pv3005w4cYJ//OMfZ90mMjKSzMzMs75vtVrP2rUvIiIiUlPfHcrjnsXbySm0E9bCj1dv60f7EI1rMVOtWkrj4+NJSkpyLaenp2O32wkLCzvnfp999hlz5szhP//5j+t+VICBAwdWa+1MSkqic+fOtSlJREREpFY+/u4IY1/bTE6hnQvatmLp5MsZEHPuLCMNr1ahdMiQIdhsNt58800AZs2aRWJiIt7e3uTn5+NwOE7b58cff2TcuHG8+OKLREVFUVRU5Oru79WrF/fccw9btmzhrbfe4rnnnmPSpEn18LVEREREqnM4DWYv/5GHPtxFWYWTkT3b8J9JlxEVpseJNgUWoyaz3//CsmXLGDduHAEBAXh5ebFu3Tp69uyJxWJhx44dXHTRRdW2nzZtGvPmzau2rnPnzmRkZJCfn8+ECRNYsWIFkZGRPPzww7UKpTabjeDgYAoKCggKCqrN1xAREZFmpLC0nKnv72TNnmwA7h/ejYdGxuGl6Z8aXE3zWq1DKUBWVhbbt28nISGB8PDw31Tob6FQKiIiIudz8HgxE9/aRmp2EVYfL579f334n4s6mF1Ws1HTvFaneQ/atm3LtddeW+fiRERERBrDN/tzue+d78gvKadNkJXXft+fvnqufZOkybhERETEIy3efJCnlv1AhdOgb8dgXru9P22C/M0uS85CoVREREQ8SrnDyV8/S2Hx5oMA/M9F7Xnmxj74+3qbXJmci0KpiIiIeIy84jLue+c7kg4cx2KBGVd2Z9LQrlgsGtDU1CmUioiIiEdIPVbIxH9v4+DxElr4efP82ItJ7NnG7LKkhhRKRURExO2t3ZPNA+/toMheQcfQABbeEU/3tq3MLktqQaFURERE3JZhGCzYcIDZy/dgGHBpTBiv3NaPsBbnfwS6NC0KpSIiIuKWSssdPPrJbj7+LhOAcQM68dSYXvj51OqBldJEKJSKiIiI28kuLOWexdvZcSgfby8LT4zqye0DO2tAkxtTKBURERG3kpxZwF3/3sZPBaUE+fvw8q39GBTb2uyy5DdSKBURERG38fn3PzH9o52UljvpEtGChXfEE9O6hdllST1QKBUREZEmz+k0eH51Ks+vTgVgaFwEL4y7mOAAX5Mrk/qiUCoiIiJNWklZBdM/3MXy5CwAJg6KYeY1PfD20v2jnkShVERERJqszPyT3PXWNlJ+suHrbeHv1/fm5v5RZpclDUChVERERJqk7QdPcM/i7eQWldG6pR+v3taP/tFhZpclDUShVERERJqcJduP8OjHuylzOOnRLogFt/ejY2ig2WVJA1IoFRERkSbD4TT4v+U/smBDOgBX9WrLczf3pYVVkcXT6U9YREREmoSj+Sf58ye7Wbs3B4ApV8Ty4BWxeGlAU7OgUCoiIiKmMAyD5EwbK388xuofj/HDURsA/r5e/POmvozq097kCqUxKZSKiIhIoyktd5C0/zirfjzG6h+zybKVut6zWCC+cxiPj+pJ747BJlYpZlAoFRERkQZ1vMjOmj3ZrPrxGBtScykpc7jeC/TzZkhsBIk92zC8ewThLa0mVipmUigVERGRemUYBvtziliZUhlEvzuUh2H8/H7bIH8Se0ZyRY82DOwSjr+vt3nFSpOhUCoiIiK/WYXDybcZeaz+8RirfjxGxvGSau/3ah9EYo82jOzZhl7tg7BYNHhJqlMoFRERkTqxlZazfl8Oq1KOsXZvDgUny13v+Xl7MbBrOIk923DFBZG0DwkwsVJxBwqlIiIiUmOHT5Scag3NZkv6ccodP/fLhwb6MuKCNozsGcmg2Ahaam5RqQX9tIiIiMhZOZ0G32cWsCqlslt+T1Zhtfe7RrQgsWcbEnu04ZJOoXhrTlGpI4VSERERASoHKJ0oLuOnglIOnShhQ2oOq37MJqfQ7trGywLx0WEk9mjDFT0i6RLR0sSKxZMolIqIiDQDhmGQV1LO0fyTZBWU8lPBSX4qKOWngtLKdbbK35dVOE/bt6XVh6FxEST2jGRYXCShLfxM+Abi6RRKRURE3JxhGBScLOdo/i/D5qlff7HOfobA+WsWC7RuaaVdsD8XRYUwsmcbLo0Jx8/HqxG+iTRntQ6lycnJTJgwgbS0NCZOnMizzz573mkdlixZwvTp0ykvL+e5555j3Lhxrvfmz5/PX//6V1q0aMHrr7/OiBEjav8tREREPJRhGNhOVvCT7SQ/5ZdytKCypbMqgGadau08We44/8GA1i39aBccQLtg/8pXSNXvK39tE+SvACqmqFUotdvtjB49miuvvJL333+fKVOmsGjRIiZMmHDWfZKTk7n11luZP38+l156KTfccAOXXHIJ3bt3Z8WKFfzxj3/k/fffJyIigttuu41vv/2W8PDw3/zFREREGoPTaXCy3FH5Kqv8taSs6vcVnCxzUlJWQWnV+l9vV7Vc5qCk3EFpmYOSU/udLKvgZLkDp3H+OgDCW/jR9lTAbB/iT9tgf9oH/xw62wRbsfpoonppmiyGYdTwRx0+/fRT/vCHP3DkyBECAwPZtWsXkydPZuPGjWfd58EHH2TPnj18+eWXADz//PPk5OTwt7/9jeuuu462bdvy6quvAjBt2jR69erFxIkTa1SPzWYjODiYgoICgoKCavo16qSswklhafn5NxSRM6rxhaa+P7eOH2z8lorPsOuZjnam2s70uWfe7kzHM07bvur3Vcf9eflX+1Tb/mzbnuVYBjhPLTgNA8Oo3Mf1e6NyD6ez8tdq6361PcbP65zGebZ3GlQ4DRxO56lfDSocp349td7hpPr7rl+dOE5bZ+BwVD+m06h+zAqn0xUgq0JlTbrE60NooG+1sNnuF2GzfUhlC6eejCRNUU3zWq1aSnft2kVCQgKBgYEA9OnTh5SUlPPuc/XVV7uWBwwYwF//+lfXe+PHj6/23vr1688aSu12O3b7zyMAbTZbbcr/Tb7NOMGtr29ptM8TERH34+/rRaCfDwG+3gT4eVf7NfAMy/5+3gRWrfPz+cXvq+8TFOCrwCker1ah1GazERMT41q2WCx4e3uTl5dHaGhojfYJCgri6NGj533vTGbPns1TTz1Vm5JFRKjr0wx/y2yLZ7rX/kzHO1NtljNtWbNVruNVHePn5ep1ufY92/vn2c/yqwN4WcDLYsFy6lcAL6/KOqrWWU7tZ7FY8LL8/J7l1HtV23ud2rBym5+P+/P2lb/38bbg7WXBx6vqVy+8qi3//OvP672qv+9twdvyy+Wf3/e2/PozKt/zrwqLvwiZgX7e+Pt446U5OkXqrFah1MfHB6vVWm2dv78/JSUlZw2lv96navvzvXcmM2fO5KGHHnIt22w2oqKiavMV6uzybq3J+L9rG+WzRERERJqbWoXSsLAwkpOTq60rLCzEz+/s85WFhYWRk5Nzxu3P9d6ZWK3W00KxiIiIiLi/Ws35EB8fT1JSkms5PT0du91OWFhYjffZsWMHHTp0OO97IiIiItJ81CqUDhkyBJvNxptvvgnArFmzSExMxNvbm/z8fByO0+dIu/HGG3n//ffZvXs3RUVFvPDCC1x55ZUA/L//9/94+eWXyczM5NixYyxcuND1noiIiIg0H7WaEgpg2bJljBs3joCAALy8vFi3bh09e/bEYrGwY8cOLrrootP2+fOf/8w///lP/P39iY2NZcOGDQQEBGAYBrfffjv/+c9/ALjiiitYtmzZeSfjr9KYU0KJiIiISO3VNK/VOpQCZGVlsX37dhISEmo80X1KSgqZmZkMHTr0tPtGv/32W4qLixk6dGiNAykolIqIiIg0dQ0aSpsKhVIRERGRpq2meU0PtxURERER0ymUioiIiIjpFEpFRERExHQKpSIiIiJiOoVSERERETFdrR4z2tRUTRxgs9lMrkREREREzqQqp51vwie3DqWFhYUAREVFmVyJiIiIiJxLYWEhwcHBZ33frecpdTqdHD16lFatWtVq0v26stlsREVFcfjwYc2Leg46TzWj81QzOk81o/NUczpXNaPzVDM6T+dnGAaFhYW0b98eL6+z3znq1i2lXl5edOzYsdE/NygoSD94NaDzVDM6TzWj81QzOk81p3NVMzpPNaPzdG7naiGtooFOIiIiImI6hVIRERERMZ1CaS1YrVb+8pe/YLVazS6lSdN5qhmdp5rReaoZnaea07mqGZ2nmtF5qj9uPdBJRERERDyDWkpFRERExHQKpSIiIiJiOoVSERERETGdQqmIiIiImE6h9BeSk5OJj48nNDSUGTNmnPcZrQBLliyhc+fOtG/fnvfee68RqjTf0qVL6dKlCz4+Plx00UX8+OOP591nzJgxWCwW1ysxMbERKjXXlClTqn3nbt26nXefr7/+mh49etC6dWvmzJnTCFWab9GiRdXOU9Vr0aJF59yvT58+1bafOHFi4xTcyHJzc4mJiSEjI8O1ri7XKvDs69WZzlNdrlXg2derM52nulyrwLOvV78+T3W9TkHzuVbVC0MMwzCM0tJSIzo62rjnnnuMtLQ045prrjHeeOONc+6ze/duw8/Pz1iwYIHx/fffG926dTP27NnTSBWbIy0tzQgNDTU++OADIysry7jpppuMyy677Lz7tWvXzti9e7eRl5dn5OXlGUVFRY1QrbkGDhxofP75567vbLPZzrl9dna2ERQUZDz11FPGvn37jEsuucRYs2ZNI1VrHrvd7jpHeXl5xuHDh43WrVsbaWlpZ92nuLjYCAwMNLKzs137lZSUNGLVjSMnJ8e49NJLDcBIT083DKNu1yrD8Ozr1ZnOU12vVYbhuderM50nw6j9tcowPPt6dabzVJfrlGE0n2tVfVEoPeWTTz4xQkNDjeLiYsMwDGPnzp3G5Zdffs59pk6dalx55ZWu5Xnz5hl//vOfG7ROs3322WfGv/71L9fymjVrjICAgHPuc+TIEaNt27YNXVqTUl5ebgQFBRmFhYU13mfu3LnGBRdcYDidTsMwDOPTTz81br311oYqscn6+9//btx1113n3Gbjxo1GQkJCI1VkniuuuMJ4/vnnq/3jWJdrlWF49vXqTOepLtcqw/Ds69WZzlNdrlWG4dnXqzOdp1+ryXXKMJrPtaq+qPv+lF27dpGQkEBgYCBQ2dyekpJy3n1GjBjhWh4wYADbt29v0DrNNmrUKO6++27X8t69e4mNjT3nPlu3bsXhcNCxY0datGjB2LFjycvLa+hSTbV7926cTicXXXQRAQEBXHXVVRw6dOic++zatYvhw4djsViA5vHz9GulpaU8//zzPProo+fcbuvWrRw5coSIiAhCQkKYNGkSdru9kapsPAsWLGDKlCnV1tXlWlW1n6der850nupyrQLPvl6d6TzV5VoFnn29OtN5+qWaXqeg+Vyr6otC6Sk2m42YmBjXssViwdvb+5wXo1/vExQUxNGjRxu0zqakrKyM5557jnvvvfec2+3Zs4e+ffvy+eefs3nzZtLT05k5c2YjVWmOlJQUunfvzuLFi/n+++/x8fGp9g/kmTT3nyeAd999l0svvZTo6Ohzbrd3714GDRrExo0bWbFiBStXrmTu3LmNU2Qj+uXPQ5W6XKvOtJ8n/Xyd6Tz9Uk2vVeDZ16sznae6XKugef881fQ6Bc3nWlVvzG6qbSr+9Kc/GdOmTau2rmPHjsaRI0fOus+AAQOMpUuXupbT0tKMbt26NViNTc0jjzxi9O3b1ygrK6vVfl9//bURHh7eQFU1TQcPHjS8vLyMgoKCs25z8803G88//7xruaKiwvDx8WmM8pqM+Ph44/PPP6/1fm+99ZbRr1+/BqioaeAX3Yh1uVYZRvO4XnGW7ta6XqsMwzOvV2c7T4ZRs2uVYTSP69XZzlNdr1OG4fnXqt9KLaWnhIWFkZOTU21dYWEhfn5+Nd7nfNt7kjVr1jB//nzeffddfH19a7VvZGQkx48fb1ZdGJGRkTidTn766aezbtOcf54A0tLSSEtLY+TIkbXeNzIykszMzAaoqumpy7XqTPs1l5+v33KtguZ3varJtQqa78/Tb7lOQfO6VtWFQukp8fHxJCUluZbT09Ox2+2EhYXVeJ8dO3bQoUOHBq2zKUhPT2fcuHHMnz+fnj17nnf7W265hY0bN7qWk5KSaNOmDVartSHLNNWMGTN49913XctJSUl4eXkRFRV11n2a689TlQ8//JBRo0bVKDgMHDiQw4cPu5aTkpLo3LlzQ5bXZNTlWnWm/ZrDz1dtr1XQ/K5XdblWQfP8eYLaXaegeV+r6sTsptqmory83IiIiHBNrTJx4kRj1KhRhmEYRl5enlFRUXHaPjt37jRatGhhfP/990ZhYaFx0UUXGf/85z8bte7GVlJSYvTs2dO46667jMLCQtfL6XQaBQUFZ+wee/rpp43+/fsbGzZsMD755BOjTZs2xpNPPmlC9Y1n8eLFRkxMjLFq1SpjxYoVRlxcnHHnnXcahmGc9Tzl5OQY/v7+xsqVK42ysjLjqquuMu6///7GLt00gwcPNhYuXFht3dn+7v3v//6vcfXVVxubN282Fi1aZLRo0cJYtGhRY5Xa6PjVaOmzXasMo3lfr355ns51rTKMs/89bA7Xq1+ep3NdqwyjeV+vOEP3/ZmuU4aha1V9USj9haVLlxqBgYFGeHi4ERERYfzwww+GYVT+YO7YseOM+zz66KOGn5+fERQUZPTr18/j5x/79NNPDeC0V3p6utG5c2fjk08+OW2fsrIy4w9/+IPRokULo23btsZTTz1llJeXN37xjeyRRx4xgoODjbCwMGPKlCmuuQ7Pdp4MwzBeeeUVw9fX1wgNDTViYmKMrKysRqzYPCUlJYafn5/x448/Vlt/tr97eXl5xnXXXWcEBAQYnTt3Nl5++eVGqtQcv/7H8WzXqqptm+v16pfn6VzXKsM4+9/D5nC9+vXP09muVYbRvK9Xvz5PZ7tOVW2ra9VvZzGMGj4KpJnIyspi+/btJCQkEB4eXqN9UlJSyMzMZOjQoc3inhppWOnp6ezZs4fBgwfTsmVLs8uRJqou1yrQ9Urql65XUp8USkVERETEdBroJCIiIiKmUygVEREREdMplIqIiIiI6RRKRURERMR0CqUiIiIiYjqFUhERERExnUKpiIiIiJhOoVRERERETKdQKiIiIiKmUygVEREREdMplIqIiIiI6RRKRURERMR0CqUiIiIiYjqFUhERERExnUKpiIiIiJhOoVRERERETKdQKiIiIiKmUygVEREREdMplIqIiIiI6RRKRURERMR0CqUiIiIiYjqFUhERERExnUKpiIiIiJhOoVRERERETKdQKiIiIiKmUygVEREREdMplIqIiIiI6RRKRURERMR0CqUiIiIiYjqFUhERERExnUKpiIiIiJhOoVRERERETKdQKiIiIiKmUygVEREREdMplIqIiIiI6RRKRURERMR0CqUiIiIiYjqFUhERERExnUKpiIiIiJjOx+wCfgun08nRo0dp1aoVFovF7HJERERE5FcMw6CwsJD27dvj5XX29lC3DqVHjx4lKirK7DJERERE5DwOHz5Mx44dz/q+W4fSVq1aAZVfMigoyORqREREROTXbDYbUVFRrtx2Nm4ZSufPn8/8+fNxOBwABAUFKZSKiIiINGHnu9XSYhiG0Ui11DubzUZwcDAFBQUKpSIiIiJNUE3zmkbfi4iIiIjpFEpFRERExHRueU9pbTidTsrKyswuQ+qJr68v3t7eZpchIiIi9cwtQ+mvBzqdTVlZGenp6TidzkaqTBpDSEgIbdu21dy0IiIiHsRjBzoZhsGhQ4coLy8/72St4h4Mw6CkpITs7GxCQkJo166d2SWJiIjIedR0oJNbtpTWREVFBSUlJbRv357AwECzy5F6EhAQAEB2djaRkZHqyhcREfEQHtt8WNW17+fnZ3IlUt+q/pNRXl5uciUiIiJSXzw2lFbRfYeeR3+mIiIinsfjQ6mIiIiINH1uGUrnz59Pz549iY+PN7uUZuvEiRMUFRWZXYaIiIjUwqHjJcz8eDcnipvedJluGUonT55MSkoK3377rdmlmGLKlCncddddruXXXnuN/fv38+9//5vrrruO0tJSHnroIQDuu+8+Fi5ceMbjPPvss5w4cYK//vWvPPjgg2RmZvK3v/0NgOuvv57ly5eftYZp06bx9ttvA/DEE09w4YUXnvF1/PhxAA4fPoyXlxfR0dHnfVksFvLz8+vjVImIiAhwJK+EmR9/z4jn1vHe1kO8tv6A2SWdxmNH37urtLQ0DMOodt9k586d8fX1dS2HhIRUm3s1LCyMW265hWnTpuHn58cHH3zgCnVff/01//M//3PGz/Ly8mLixIn0798fPz8/Xn/9dSwWCw6Hg9WrV/N///d/Z60zICAAf39/oHIk/GOPPcbYsWOrbRMdHe0aaObr60tgYCAZGRkA2O12rrzySl588UV69+5dbT+LxaIBaiIiIvXgp4KTzF+bxgffHqbcUTkL6ODY1lzZq43JlZ1OobSJee655zh27JhrXtWPP/6Y7OxswsLCXOuqfq2oqMDhcGAYBtdffz27d+8mKyuLtLQ0unfvzq5du0hLS2PIkCFA5dOtysvLsVqtnDhxgk6dOlFRUcHevXspKiqiXbt29OjRg3Xr1hEcHEz37t2BypkMHA4Hfn5+bNq0iQMHDpCWlobFYsHLy+ucDzGoCte/DplPP/0069evZ/To0a51r776KldddVW17ygiIiK1d8xWyivr9vPulkOUOSobsi7vFs60xDj6R4eZXN2ZNZtQahgGJ8vP/QSohhLg613jEeOvvPKK6/fp6el89913PProoyxbtszVMpmfn4/D4eDjjz/mmWeeYdWqVRQUFLB06VK6du1KdnY2mZmZ5OTk4OvrS48ePbDb7eTl5XH77bfz2muvUVBQwBdffMGRI0dYvXo1F110EWFhYWzZsoVdu3ZRWFhIdHQ0xcXFnDx5kj/96U888cQT7N+/n82bN1cLzk6nkxkzZvC3v/2N48ePk5WVRa9evVwhGKqHzKVLl/LMM8/w5z//maeffpoXXniBpUuXcuWVV9bXKRcREWmWcgrtvPr1ft7efBB7RWUYHRATxkMj40joEm5ydedm+hOdDh48yMSJEykuLmbo0KHMnj27xvue6wkBpaWlpKenExMTg7+/PyVlFfR8YkV9l18jKX+9kkC/muX/Z555Bj8/P6ZNm8aHH37Ip59+yrvvvlttmyeffJLc3FxeeukloPJ+zeuvv56oqCgcDgfFxcW888473HbbbSQkJPC3v/2N5cuXM3/+fP773/+6jpOcnMxNN91Ely5dCAsLIzs7myVLlnDxxRfzyCOPMHHiRF555RV++OEH12dVuffee+nfvz8Wi4XvvvuOwYMHM3bsWHbu3Mn999/Pxo0bq22fn59Px44dOXHiBCNGjOCZZ57h/vvvp2fPnuzYsYN169YRGRkJVLaunjx50hXCf+3Xf7YiIiLN3fEiO6+tP8BbSRmUlleG0X6dQ3loZByXdQ03dTpFt3mi04svvshf/vIXBg0axLXXXsvhw4eJiooyuyzTjBs3jmHDhtGmTRu+/PJLRowYQXp6Ok8//TRvvPHGadsnJydz7bXX8vzzz1NWVsYnn3zCbbfdxsMPP8y6deuIiIgA4OjRo7Rv396136pVq7j77rtZvHgxSUlJ5Obm0rdvXyZPnkx6ejr79+8/435Q2eqck5PD9OnTmTBhAidPnuSBBx7gkUceoby8nOPHjxMdHY1hGLRr147Nmze79vXz82PDhg0kJyfTunVrvvrqK7p27cr27dv53e9+pyc0iYiI1EJecRkLNhxg0TcZlJRV9gj3jQrhoZFxDIlt7VZzezdIKM3NzSU+Pp61a9cSHR0NVIanCRMmkJaWxsSJE3n22WexWCyEhoaSkpLCBRdcwPHjxwkLa5j7HAJ8vUn5qzndwwG+NQ9anTp14osvvmDo0KGUlZXxj3/8g7CwMNatW8eKFStO6+Lu2bMn27Zto2XLlvTo0YP169fTqVMnbDYbHTt2dLWyHjhwgLi4ONd+w4YNY+vWrZSUlHDHHXewY8cOWrVqxZNPPsmf/vQnNm3a5Nrv+uuvd+33zTffMGPGDJKSknjuueeYNm0aN998Mx988AEjRowgOTmZ+++/n3Xr1mEYBqWlpdXq3bt3LzfddBP5+fnccccdPP3006SmpvLggw9y9OhRPvvss1qfXxERkeam4GQ5Czcc4I1NGRTZKwC4sEMQD42MY3j3SLcKo1XqfTRJbm4uo0aNco2yhsqR1qNHj6Zfv35s27aNlJQUFi1aBMB1113HRx99xCuvvMLw4cMb7Dn1FouFQD8fU161/cG44IILuPXWW10j7H19fZkxYwZPPvnkadsmJSXRu3dv2rVrR15eHkOGDCEsLIyPP/6Yv//977Rp04YdO3awceNGLrvsMtd+H330EX369KFnz57k5eXRu3dvgoKCyM7OZtasWRw8eJBjx46xadOmavt9/vnndOnShTvuuIPQ0FCgcs7Sqq73X5/zqmfVV+nevTtz5swhPT2d+Ph4rrvuOl5++WW+/PJLVqxYwdChQ2t1rkRERJqTwtJyXlidyqBn1vDCmjSK7BVc0LYVr/2+H5/dP4gRF7Rxy0AKDRBKx44dy/jx46utW758OQUFBcyZM4euXbsya9Ys19yZzzzzDC+//DKPP/447dq1Y8WKs9/3abfbsdls1V6eKCMjg7fffpsbbriBiRMnAnDrrbcyfvz4alNBAVx++eVkZWXRu3dvli1bRkZGBoMHD+b2228H4M4772T69Ons3buX/v37u/YbN24cBw8epEOHDmzZsoWMjAy6dOnC73//eywWC+PGjWP8+PGEhIRU675/9NFHWbx4MVar1bVuz5497Ny5k9atW3PnnXdSVFRE//79CQwM5MCB0+dBS0xM5PvvvyctLY0NGzbw+9//no4dO3LZZZe57V8kERGRhlRkr2D+2jQGPbOWOSv3UVhaQVyblrxy6yV8MWUwv+vV1u3/Da33ULpgwQKmTJlSbd2uXbtISEhwtYL26dOHlJQUAAoLC0lJScHpdLJt27ZzntDZs2cTHBzsennivaeFhYXcdNNNPP744/zrX/8iNTWVt956i6CgIB544IEzTpWUmZmJn58fDz74ILfeeiubN29mzJgxANx+++1s3ryZcePGnTYtU0pKChEREYwfP54bbrgBwzAYMGAAUDmQac2aNUyYMKHaPi1atKi2fPjwYTp06EBISAijRo1i27ZtrldcXJzrMysqKqrtV1FRQVJSEn379uXTTz/l4MGD1d7/dfgWERFpjkrKKvjX1/sZ8uxa/rFiLwUny+ka0YIXx13Ml1OHcHXvdnh5uXcYrVLvoTQmJua0dTabrdp6i8WCt7c3eXl5PPzwwzzyyCMEBwdz8uRJrrjiirMee+bMmRQUFLhehw8fru/yTZWTk8Pw4cPp27cvDzzwAH5+frz00kvY7fZq25WXl1cLpx06dGD16tU89thjrF69miuuuILLL7+c4uJiJk2axCWXXMK///1v132iVfr27cvGjRu57bbb2LlzJ126dGH06NGcOHGCe++9l2HDhvHss8+yZ8+e02qtqKggMDCQTz/91BWAz6RqcoeqqaGqxMfH89FHH3Ho0CESExNPG0z16xArIiLSnJSWO3h9wwGGPLuW2cv3cKK4jJjWLZh3y0V8NW0oo/u295gwWqVRRt/7+PhU6+4FKqdpKikhISGBH3/8sUbHsVqtWK1W5s+fz/z58885abs7KiwsJDExkb///e+udYmJia7f5+XlMWbMGHbs2MHzzz8PQHFxMe+++y7vvPMO/v7+fPPNN3Tp0oW33nqLvn37cs011/D111/z3nvv8bvf/Y5Zs2YxdepUcnNzeeedd1i8eDFxcXFs3ryZ1q1b8/zzz9OnTx8mT57MzJkzmT17NpdeeikLFizg5ptvBiofT+pwOBgyZAj/8z//wyeffEJSUhJLly7lwgsvdNW7f/9+V6CuqKiguLiYkJCQM373WbNmVVtWKBURkeaotNzB+1sPMX/dfnIKK/8NjQoLYMqIWK6/uAM+3p77cJkGm6fUYrGQnp5OdHQ0zzzzDMnJySxevNj1fkhICKmpqa4pi+qiNvOUeoqPPvqIuLg4+vbt61o3d+5cBg0aRHx8vGvdhx9+SIcOHbj88std65KSkmjdujWxsbFUVFTw7LPPcv3119OjRw/XNgsWLOCyyy6jV69ernVffPEFAwYMoHXr1metq+rpUr/+z0cVh8PBsWPHTmsRrQtP/bMVEZHmy17h4MNtR5i/Jo0sW+XMNR1CAnhgRDdu7NcRXzcOozWdp7RRQumaNWu4++67SUtLAyqfVNSzZ0+KiorqNC/lL1tK9+3b16xCqejPVkREPEe5w8mS7Ud4aU0amfknAWgX7M/k4d24uX8Ufj7uG0arNKnJ84cMGYLNZuPNN99kwoQJzJo1i8TExDpPlD558mQmT57s+pLnYvIDq6QB6M9URETcXYXDySc7MnlhTSqHT1SG0chWViYP78Yt8VH412KOc0/RaPeUvv7664wbN44ZM2bg5eXFunXr6ny8mtxTWhV4y8rKTpsrU9xbSUkJUDl/q4iIiDtxOA2W7crk+VWpZByv/PesdUs/Jg3rxq2XdmqWYbRKg3Xfn0lWVhbbt28nISGB8PDw33y8czUHG4bBoUOHKC8vp3379mecSknci2EYlJSUkJ2dTUhICO3atTO7JBERkRpxOA0+3/0T81bt40BOMQBhLfy4Z0gXfj+wM4F+pj/5vcGYfk9pQ6rJPaVQ2Uqanp6uOS89TEhICG3buv8kwSIi4vmcToMvf8hi3qp97DtWBEBIoC93D+nCHQOjaWH13DBaxaNDaZWafEmn00lZWVkjVyYNxdfXt873IouIiDQWwzD4KuUYc1fuY09WIQBB/j7cNbgLd14eTSv/5nMLWpMa6GQmLy8vjdAWERGRRmEYBmv2ZDN31T6SMysfh97S6sMfBsXwv4NiCA5oPmG0ttwylHrq5PkiIiLingzD4Ot9OcxduY9dRwoACPTzZsLl0dw1uAshgX7nOYJ4fPe9iIiISEMxDINNaceZs3Iv3x3KByDA15vbL+vMPUO6EtZCYVTd9yIiIiINaPOB48xZuY+t6ScAsPp48fuEztwztCsRrc78hEM5O7cMpeq+FxEREbNsyzjBnJX7+Gb/cQD8fLwYP6AT9w3rSmSQxrHUlbrvRURERGrgu0N5zF25jw2puQD4elsYG9+J+4Z3pV2wHtRzNuq+FxEREakH3x/JZ+7KfazdmwOAj5eFm/pHMXl4VzqGBppcnedQKBURERE5gx+OFjB3ZSqrfjwGgLeXhRsv6cADI2KJClMYrW9uGUp1T6mIiIg0lL1ZhcxduY8vf8gCwMsC113UgQeuiCWmdQuTq/NcuqdUREREBEjLLmTeqlQ+3/0ThgEWC4zu054pV8TSLbKl2eW5Ld1TKiIiIlIDB3KKeGF1Kkt3HaWqqe7a3u2YmhhLXJtW5hbXjCiUioiISLN08HgxL6xO45MdR3CeCqNX9mrDg4lx9GinHtjGplAqIiIizcrhEyW8tCaNJd8dwXEqjV5xQSTTRsZxYYdgk6trvhRKRUREpFk4mn+Sl9am8eG3h6k4FUaHdY9gWmIcfaNCzC1OFEpFRETEs2UVlPLyujTe33qYMocTgMGxrXkwMY5+nUNNrk6quGUo1ZRQIiIicj7ZhaW8sm4/72w5RFlFZRgd2CWcaSPjGBATZnJ18muaEkpEREQ8yvEiO69+vZ/Fmw9SWl4ZRuOjQ5k2Mo7LurY2ubrmR1NCiYiISLOSV1zGaxsO8NY3GZSUVfamXtwphOkju3N5t3AsFovJFcq5KJSKiIiIWysoKef1jQd4Y2M6xafCaN+OwUwbGcfQuAiFUTdhaih9/vnn+eSTTwA4duwYv//973n00UfNLElERETchK20nDc2prNwQzqF9goAerUP4qGRcYy4IFJh1M00mXtKx48fzzPPPENUVFSN99E9pSIiIs1Pkb2CRZvSeW39AWyllWH0gratmDYyjt/1bKMw2sTUNK951fcH5+bmEhMTQ0ZGhmtdcnIy8fHxhIaGMmPGDH6dg3fv3k1ISEitAqmIiIg0L8X2Cl5Zt5/Bz6zhn1/tw1ZaQWxkS16+9RK+mDKYK3u1VSB1Y/UaSnNzcxk1alS1QGq32xk9ejT9+vVj27ZtpKSksGjRomr7vfTSS9x///31WYqIiIh4iJNlDhasP8CQZ9fyzJd7yCspp0tEC14YdzFfPjiEa3q3w8tLYdTd1es9pWPHjmX8+PFs2bLFtW758uUUFBQwZ84cAgMDmTVrFpMnT2bChAkAlJaWsm/fPnr27FmfpYiIiIibKy138O6WQ7y8bj+5RXYAosMDmZoYy5i+HfBWEPUo9RpKFyxYQExMDFOnTnWt27VrFwkJCQQGBgLQp08fUlJSXO9/9dVXDB8+vEbHt9vt2O1217LNZqunykVERKSpsFc4+ODbw8xfm8YxW+W/+x1DA5hyRSw3XNwBH+96v/tQmoB6DaUxMTGnrbPZbNXWWywWvL29ycvLIzQ0lJUrV3LDDTfU6PizZ8/mqaeeqrd6RUREpOkoq3CyZPsRXlqTytGCUgDaB/vzwBWx3HhJR/x8FEY9WYNPCeXj44PVaq22zt/fn5KSEkJDQ3nxxRdrfKyZM2fy0EMPuZZtNpsGR4mIiLi5coeTT77L5IU1qRzJOwlA2yB/Jo/oxs39O2L18Ta5QmkMDR5Kw8LCSE5OrrausLAQPz+/Wh/LarVitVqZP38+8+fPx+Fw1FeZIiIi0sgqHE6W7jzKC2tSOXi8BICIVlYmD+vK2AGd8PdVGG1OGjyUxsfHs2DBAtdyeno6drudsLCwhv5oERERaYIcToP/fn+U51elciC3GIDWLf24d2hXbkvorDDaTDXI5PkWi4X09HSio6OpqKigffv2PPPMM0yYMIG77rqLrKwsPvvss9/8OZo8X0RExH04nQZfJP/EvFWppGUXARAa6Mu9Q7vy+4GdCfTT0889UU3zWqPcU/r6668zbtw4ZsyYgZeXF+vWrftNx1T3vYiIiPtwOg2+Ssli7spU9h4rBCA4wJe7h3ThjsuiaWlVGJVGfMxoVlYW27dvJyEhgfDw8Ho5plpKRUREmi7DMFj1YzZzV+4j5afKaRxb+fswcVAXJgyKJsjf1+QKpTE0mZbSKm3btuXaa69trI8TERERkxiGwbq9OcxdtY/vjxQA0NLqwx8uj+Z/B3UhOFBhVE7nlu3l6r4XERFpegzDYENqLnNW7mPn4XwAAv28ufOyaO4a3IXQFrWfeUeaj0brvm8I6r4XERFpGr5Jqwyj2w7mAeDv68UdA6O5e0gXwltaz7O3eLIm131fn9RSKiIi0jRsOXCcuav2sfnACQCsPl7cltCZe4Z2IbKVv8nViTtRS6mIiIjU2vaDJ5i7MpWNabkA+Hl7MW5AFPcN70abIIVR+ZlHt5SKiIiIOXYezmfuyn18vS8HAF9vCzf3j2Ly8G60DwkwuTpxZwqlIiIicl7JmQXMXbmP1XuyAfD2snBTv45MHt6NqLBAk6sTT+CWoVT3lIqIiDSOlKM25q3ax1cpxwDwssANl3TkgRHd6BzewuTqxJPonlIRERE5zb5jhcxbtY8vdmcBYLHA//Rtz5QrYukS0dLk6sSd6J5SERERqbW07CKeX53Kf78/imFUhtFre7fjwcRYukW2Mrs88WAKpSIiIkJ6bjEvrE5l6c5MnKf6UK/q1ZYHR8ZyQVv1RkrDc8tQqntKRURE6seh4yW8uCaVj3dk4jiVRkf2bMODibH0ah9scnXSnOieUhERkWboSF4J89em8dG2I1ScCqMjLohkWmIcvTsqjEr90T2lIiIicpqfCk4yf20aH3x7mHJHZRgdEhfBtMRYLu4UanJ10pwplIqIiDQD2bZSXl63n3e3HKLM4QTg8m7hTEuMo390mMnViSiUioiIeLScQjuvfr2ftzcfxF5RGUYHxITx0Mg4ErqEm1ydyM8USkVERDzQ8SI7r60/wFtJGZSWV4bRfp1DmT4yjoFdw7FYLCZXKFKdW4ZSjb4XERE5s7ziMhZsOMCibzIoKav8d7JvVAgPjYxjSGxrhVFpsjT6XkRExAMUnCxn4YYDvLEpgyJ7BQAXdgjioZFxDO8eqTAqptHoexERkWagsLScNzdlsGDDAQpLK8Noj3ZBTEuMZWTPNgqj4jYUSkVERNxQsb2CRd9UhtH8knIA4tq0ZFpiHFf2aouXl8KouBeFUhERETdSUlbB4qSD/Gv9AU4UlwHQNaIFDybGcW3vdgqj4raaRCj9/e9/zz333MOgQYPMLkVERKRJKi138Pbmg7z69X5yiyrDaEzrFky9IpbRfdvjrTAqbs70ULpy5Uq8vb0VSEVERM6gtNzB+1sP8fK6/WQX2gHoFBbIlCtiue6i9vh4e5lcoUj9qPef5NzcXGJiYsjIyHCtS05OJj4+ntDQUGbMmEHVgP+ysjLuu+8+2rVrx8qVK+u7FBEREbdlr3CwePNBhv9zHU9+lkJ2oZ0OIQE8c2NvVk8fyv/r11GBVDxKvf405+bmMmrUqGqB1G63M3r0aPr168e2bdtISUlh0aJFAPz73/+mf//+TJ06lY8//piPP/64PssRERFxO+UOJ+9tPcSIf37N458m81NBKe2C/fn79Rey9o/DuCW+E74Ko+KB6vWneuzYsYwfP77auuXLl1NQUMCcOXPo2rUrs2bNYuHChQDs3LmTiRMn0rZtW26++WbWrVtXn+WIiIi4jQqHk4+2HWbEc+uY+fFuMvNPEtnKylNjerFuxjBuvbQzfj4Ko+K56vWe0gULFhATE8PUqVNd63bt2kVCQgKBgYEA9OnTh5SUFAC6detGeno6AN999x2dO3c+5/Htdjt2u921bLPZ6rN8ERGRRudwGizblcnzq1LJOF4CQOuWfkwa1o1bL+2Ev6+3yRWKNI56DaUxMTGnrbPZbNXWWywWvL29ycvL4w9/+AN33nknixYtwtfXl08//fScx589ezZPPfVUfZYsIiJiCqfT4L+7f+L5VfvYn1MMQFgLP+4d2oXbEjoT6Gf6WGSRRtXgP/E+Pj5YrdZq6/z9/SkpKaFDhw61uo905syZPPTQQyxYsIAFCxbgcDhIS0ur75JFREQajNNp8OUPWcxbtY99x4oACAn05e4hXbhjYDQtrAqj0jw1+E9+WFgYycnJ1dYVFhbi5+dX62NZrVasVivTp09n+vTprmepioiINHWGYfBVyjHmrtzHnqxCAIL8fbhrcBfuvDyaVv6+JlcoYq4GD6Xx8fEsWLDAtZyeno7dbicsLKzOx5w/fz7z58/H4XDUR4kiIiINxjAM1uzJZu6qfSRnVo6FaGn14Q+DYvjfQTEEByiMigBYjKpJQ+vzoBYL6enpREdHU1FRQfv27XnmmWeYMGECd911F1lZWXz22We/+XOqWkoLCgoICgqqh8pFRETqh2EYfL0vh7kr97HrSAEAgX7eTLg8mrsGdyEksPY9hiLuqKZ5rVHuKX399dcZN24cM2bMwMvL6zdP/aSWUhERaaoMw2BT2nHmrNzLd4fyAQjw9eb2yzpzz5CuhLVQGBU5kwZpKT2TrKwstm/fTkJCAuHh4fVyTLWUiohIU7L5wHHmrNzH1vQTAFh9vPh9QmfuGdqViFbW8+wt4pmaTEtplbZt23LttdfWy7HUUioiIk3JtxknmLtyH9/sPw6An7cX4y/txH3DuhIZ5G9ydSLuodFaShuCWkpFRMRM3x3KY+7KfWxIzQXA19vC2PhO3De8K+2CA0yuTqRpaHItpSIiIp7i+yP5zF25j7V7cwDw8bJwU/8oJg/vSsfQQJOrE3FPbhlK1X0vIiJm+OFoAXNXprLqx2MAeHtZuPGSDjwwIpaoMIVRkd9C3fciIiLnsSfLxryVqXz5QxYAXha47qIOPHBFLDGtW5hcnUjTpu57ERGR3yj1WCHzVqfy+fc/AWCxwOg+7ZlyRSzdIluaXJ2IZ1EoFRER+ZX9OUW8sDqVZbuOUtWfeG3vdkxNjCWuTStzixPxUG4ZSnVPqYiINISDx4t5fnUqn+7IxHkqjF7Zqw0PJsbRo51uExNpSLqnVEREmr3DJ0p4aU0aS747guNUGk3sEcmDiXFc2CHY5OpE3JvuKRURETmPzPyTzF+bxoffHqbiVBgd1j2CBxPjuCgqxNziRJoZhVIREWl2sgpKeXldGu9vPUyZwwnA4NjWPJgYR7/OoSZXJ9I8uWUo1T2lIiJSF9mFpbyybj/vbDlEWUVlGE3oEsZDI7szICbM5OpEmjfdUyoiIh4vt8jOv77ez+LNByktrwyj8dGhTBsZx2VdW5tcnYhn0z2lIiLS7J0oLuO19Qd465sMTpZX9q5d3CmEh0bGMahbaywWi8kVikgVhVIREfE4+SVlvL4hnTc3pVNcVhlG+3QMZtrIOIbFRSiMijRBCqUiIuIxbKXlvLExnYUb0im0VwDQs10QD42M44oekQqjIk2YQqmIiLi9InsFizal89r6A9hKK8PoBW1b8WBiHFf2aqMwKuIG3DKUavS9iIgAFNsr+HfSQf61fj/5JeUAxEa25MHEOK6+sC1eXgqjIu5Co+9FRMTtnCxz8Pbmg7z69X6OF5cB0KV1C6YmxjKqT3u8FUZFmgyNvhcREY9TWu7g3S2HeHndfnKL7AB0Dg9k6hWxjOnbHh9vL5MrFJG6UigVEZEmz17h4INvDzN/bRrHbJVhtGNoAFOuiOWGizsojIp4AIVSERFpssoqnHy0/TAvrUnjp4JSANoH+/PAFbHceElH/HwURkU8hemhtLCwkB49etCtWzcAPv74Y8LC9Kg3EZHmrNzh5OPvjvDC6jQy808C0DbIn8kjunFz/45YfbxNrlBE6pvpoXT79u1MnTqVGTNmmF2KiIiYrMLhZOnOo7ywJpWDx0sAiGhl5b5hXRk3oBP+vgqjIp6qQfo9cnNziYmJISMjw7UuOTmZ+Ph4QkNDmTFjBlWD/rds2cKbb77JwIEDeeihhxqiHBERaeIcToOlOzP53dz1TP9oFwePlxDewo/Hru3B+hnDmXB5jAKpiIer91Cam5vLqFGjqgVSu93O6NGj6devH9u2bSMlJYVFixYBMHjwYDZu3EhSUhJ79+4lJSWlvksSEZEmyuk0+O/3R7ly3nqmvr+TA7nFhAb68sjVF7Dh4eFMHNyFAD+FUZHmoN6778eOHcv48ePZsmWLa93y5cspKChgzpw5BAYGMmvWLCZPnsyECRPo168fVqsVgAsuuIDU1FR69ux5xmPb7Xbsdrtr2Waz1Xf5IiLSCJxOg69Sspi7MpW9xwoBCA7w5e4hXbjjsmhaWk2/u0xEGlm9t5QuWLCAKVOmVFu3a9cuEhISCAwMBKBPnz6uFtFbbrmFAwcOcPLkSb766isuvPDCsx579uzZBAcHu15RUVH1Xb6IiDQgwzBYmXKMUS9u5N63v2PvsUJa+fswLTGODQ8PZ/LwbgqkIs1Uvf/Nj4mJOW2dzWartt5iseDt7U1eXh5//vOfGTVqFD4+PkyaNImuXbue9dgzZ86sdt+pzWZTMBURcQOGYbBubw5zV+3j+yMFALS0+vCHy6P530FdCA70NblCETFbo/x31MfHx9VFX8Xf35+SkhLi4+NrfB+p1WrFarUyf/585s+fj8PhaIhyRUSknhiGwYbUXOas3MfOw/kABPp5c+dl0dw1uAuhLfzMLVBEmoxGCaVhYWEkJydXW1dYWIifX90uRpMnT2by5MmuZ6mKiEjT801aZRjddjAPAH9fL+4YGM3dQ7oQ3tJ6nr1FpLlplFAaHx/PggULXMvp6enY7fY6T5KvllIRkaZry4HjzF21j80HTgBg9fHitoTO3DO0C5Gt/E2uTkSaKotRNWFofR/YYiE9PZ3o6GgqKipo3749zzzzDBMmTOCuu+4iKyuLzz777Dd9RlVLaUFBAUFBQfVUuYiI1MX2gyeYuzKVjWm5APh5ezH+0k5MGtaVNkEKoyLNVU3zWqPdU/r6668zbtw4ZsyYgZeXF+vWravz8dRSKiLSdOw8nM/clfv4el8OAL7eFm7uH8Xk4d1oHxJgcnUi4i4arKX0TLKysti+fTsJCQmEh4f/5uOppVRExDzJmQXMXbmP1XuyAfD2snBTv45MHt6NqLBAk6sTkaaiSbWUVmnbti3XXnvtbz6OWkpFRMyTctTGvFX7+CrlGABeFrjhko48MKIbncNbmFydiLirRm0prW9qKRURaTz7jhUyb9U+vtidBYDFAtdd1IEHRnSjS0RLk6sTkaaqSbaUioiI+0nLLuL51an89/ujGEZlGB3Vpz1Tr+hGt8hWZpcnIh7CLUOpuu9FRBpeem4xL6xOZenOTJyn+tSu6d2WqVfE0b2twqiI1C9134uISDWHjpfw4ppUPt6RieNUGh3Zsw3TEuPo2V7XWhGpHXXfi4hIrRzJK2H+2jQ+2naEilNhdMQFkUxLjKN3Rz09T0QalluGUnXfi4jUn58KTjJ/bRoffHuYckdlGB0SF8G0xFgu7hRqcnUi0lyo+15EpJk6ZivllXX7eXfLIcocTgAu7xbOtMQ4+kfX7THQIiK/pu57ERE5o5xCO69+vZ+3Nx/EXlEZRgfEhPHQyDgSuvz2B5uIiNSFQqmISDNxvMjOa+sP8FZSBqXllWG0X+dQHhoZx2Vdw7FYLCZXKCLNmUKpiIiHyysuY8GGAyz6JoOSssp78ftGhfDQyDiGxLZWGBWRJsEtQ6kGOomInF/ByXIWbjjAG5syKLJXAHBhhyAeGhnH8O6RCqMi0qRooJOIiIcpLC3nzU0ZLNhwgMLSyjDao10Q0xJjGdmzjcKoiDQqDXQSEWlmiuwVvPVNBq+tP0DByXIA4tq0ZFpiHFf2aouXl8KoiDRdCqUiIm6upKyCxUkH+df6A5woLgOga0QLHkyM49re7RRGRcQtKJSKiLip0nIHb28+yKtf7ye3qDKMxrRuwdQrYhndtz3eCqMi4kYUSkVE3ExpuYP3tx5i/rr95BTaAYgKC+CBEbHccHEHfLy9TK5QRKT23DKUavS9iDRH9goHH247wvw1aWTZSgHoEBLAAyO6cWO/jvgqjIqIG9PoexGRJq7c4WTJ9iO8tCaNzPyTALQL9mfy8G7c3D8KPx+FURFpujT6XkTEzVU4nHy8I5MX16Ry+ERlGI1sZWXy8G7cEh+Fv6+3yRWKiNQfhVIRkSbG4TRYtiuT51elknG8BIDWLf2YNKwbt17aSWFURDxSkwilKSkpPPjgg3z11VdmlyIiYhqn0+C/u3/i+VX72J9TDEBYCz/uHdqF2xI6E+jXJC7ZIiINoklc4aZPn05ZWZnZZYiImMLpNPjyhyzmrdrHvmNFAIQE+nL3kC7cMTCaFtYmcakWEWlQ9X53fG5uLjExMWRkZLjWJScnEx8fT2hoKDNmzOCXY6veeecdLr/88vouQ0SkyTMMgxU/ZHHNCxu4753v2HesiCB/H6aPjGPDn4Zz37BuCqQi0mzUayjNzc1l1KhR1QKp3W5n9OjR9OvXj23btpGSksKiRYuAytFYCxcu5E9/+lN9liEi0qQZhsHqH48x+qWN3LN4O3uyCmlp9WHKFbFseHgED1wRSyt/X7PLFBFpVPX6X/CxY8cyfvx4tmzZ4lq3fPlyCgoKmDNnDoGBgcyaNYvJkyczYcIE/vKXv/CXv/wFPz+/+ixDRKRJMgyD9am5zFm5j12H8wEI9PNmwuXR3DW4CyGBuhaKSPNVr6F0wYIFxMTEMHXqVNe6Xbt2kZCQQGBgIAB9+vQhJSUFgPXr17Njxw4Adu7cyV/+8heeeuqpsx7fbrdjt9tdyzabrT7LFxFpEIZh8M3+48xZuY/tB/MACPD15vbLOnPPkK6EtVAYFRGp11AaExNz2jqbzVZtvcViwdvbm7y8PLZv3+5aP2zYsHMGUoDZs2efdxsRkaZk84HKMLo1/QQAVh8vfp/QmXuGdiWildXk6kREmo4Gv4Pex8cHq7X6hdff35+SkhJCQ0Nd69atW3feY82cOZOHHnrItWyz2YiKiqq3WkVE6su2jBPMWbmPb/YfB8DPx4vxAzpx37CuRAb5m1ydiEjT0+ChNCwsjOTk5GrrCgsL63QfqdVqxWq1Mn/+fObPn4/D4aivMkVE6sV3h/KYu3IfG1JzAfD1tjA2vhP3De9Ku+AAk6sTEWm6GjyUxsfHs2DBAtdyeno6drudsLCwOh9z8uTJTJ482fUsVRERs31/JJ+5K/exdm8OAD5eFm7qH8X9I7rRIURhVETkfBo8lA4ZMgSbzcabb77JhAkTmDVrFomJiXh71/0xeWopFZGm4oejBcxblcrKlGMAeHtZuPGSDtw/PJZO4YEmVyci4j4sxi9nsq+vg1ospKenEx0dDcCyZcsYN24cAQEBeHl5sW7dOnr27PmbP6eqpbSgoICgoKDffDwRkZram1XIvFX7WJ6cBYCXBa67qAMPXBFLTOsWJlcnItJ01DSvNUhL6a9z7pgxY9i/fz/bt28nISGB8PDw33R8tZSKiFnSsguZtyqVz3f/hGGAxQKj+7RnyhWxdItsaXZ5IiJuq0FaShuLWkpFpLEcyCnihdWpLN11lKqr5rW92zE1MZa4Nq3MLU5EpAkztaW0oamlVEQay8HjxbywOo1PdhzBeSqMXtmrDQ8mxtGjnf4zLCJSX9RSKiJyBodPlPDSmjSWfHcEx6k0mtgjkgcT47iwg2b9EBGpKY9uKRURaShH80/y0to0Pvz2MBWnwuiw7hFMS4yjb1SIucWJiHgwtwyl6r4XkfqWVVDKy+vSeH/rYcocTgAGx7bmwcQ4+nUOPc/eIiLyW6n7XkSatezCUl5Zt593thyirKIyjA7sEs60kXEMiKn7Qz5ERKSSuu9FRM7heJGdV7/ez+LNByktrwyj8dGhTBsZx2VdW5tcnYhI8+OWoVTd9yJSV3nFZby24QBvfZNBSVnlNeTiTiFMH9mdy7uFY7FYTK5QRKR5Uve9iDQLBSXlvL7xAG9sTKf4VBjt2zGYaSPjGBoXoTAqItJA1H0vIgLYSst5Y2M6CzekU2ivAKBX+yAeGhnHiAsiFUZFRJoIhVIR8UhF9goWbUrntfUHsJVWhtEL2rZi2sg4ftezjcKoiEgT45ahVPeUisjZFNsr+HfSQV5bv5+8knIAYiNbMm1kHFf1aouXl8KoiEhTpHtKRcQjnCxz8Pbmg7z69X6OF5cB0CWiBVOviGVUn/Z4K4yKiJhC95SKSLNQWu7g3S2HeHndfnKL7ABEhwcyNTGWMX07KIyKiLgJhVIRcUv2CgcffHuY+WvTOGarDKMdQwOYckUsN1zcAR9vL5MrFBGR2lAoFRG3Ulbh5KPth5m/Jo2jBaUAtA/254ErYrnxko74+SiMioi4I4VSEXEL5Q4nH393hBdWp5GZfxKAtkH+TB7RjZv7d8Tq421yhSIi8lu4ZSjV6HuR5qPC4WTpzqO8sCaVg8dLAIhoZWXysK6MHdAJf1+FURERT6DR9yLSJDmcBv/9/ijPr0rlQG4xAOEt/Jg0rCu3JXRWGBURcRMafS8ibsnpNPgi+SfmrUolLbsIgNBAX+4Z2pXbB3Ym0E+XLRERT6Sru4g0CU6nwVcpWcxdmcreY4UABAf4cveQLtxxWTQtrbpciYh4Ml3lRcRUhmGw6sds5q7cR8pPNgBa+fswcVAXJgyKJsjf1+QKRUSkMTSJUJqdnc3333/PpZdeSqtWrcwuR0QagWEYrNubw5yV+9idWQBAS6sPf7g8mv8d1IXgQIVREZHmxPRQmp6ezu23387IkSN59NFH+eabb/DxMb0sEWkghmGwITWXOSv3sfNwPgCBft7ccVk0dw/uQmgLP3MLFBERU5ie/n744QdeffVVevXqxffff09mZiadO3c2uywRqWeGYZC0/zhzVu5j28E8APx9vbh9YDR3D+lC65ZWkysUEREzNcijT3Jzc4mJiSEjI8O1Ljk5mfj4eEJDQ5kxYwZVM1GNGjWKCy64gOXLl2Oz2ejUqVNDlCQiJtpy4DhjX9vM+Ne3sO1gHn4+Xvzh8hjW/2k4j17TQ4FURETqP5Tm5uYyatSoaoHUbrczevRo+vXrx7Zt20hJSWHRokWu90+ePMmHH35IWFhYfZcjIibafvAEt76+mVte28yW9BP4eXtxx8DObPjTcJ4Y3ZPIVv5mlygiIk1EvYfSsWPHMn78+Grrli9fTkFBAXPmzKFr167MmjWLhQsXut5v2bIlb775Jr6+vuzcufOsx7bb7dhstmovEWl6dh7O5443tnLjK0lsSjuOr7eF8Zd2Yt2MYTz1PxfSJkhhVEREqqv3e0oXLFhATEwMU6dOda3btWsXCQkJBAYGAtCnTx9SUlIAeOyxxxgwYABjxozh+PHj5xx9P3v2bJ566qn6LllE6klyZgFzV+5j9Z5sALy9LNzUryOTh3cjKizQ5OpERKQpq/eW0piYmNPW2Wy2austFgve3t7k5eVx//3389xzzzFo0CAGDhxIt27dznrsmTNnUlBQwD//+U+6d+9+zm1FpPGkHLVx97+3MerFjazek42XBW68pCNrpg/l/27so0AqIiLn1Sij7318fLBaqw9k8Pf3p6SkhA4dOvD111/X6DhWqxWr1cr06dOZPn2661mqImKOfccKmbdqH1/szgLAYoH/6dueKVfE0iWipcnViYiIO2mUUBoWFkZycnK1dYWFhfj51W0+wvnz5zN//nwcDkd9lCcitZSWXcTzq1P57/dHMYzKMHpt73Y8mBhLt0g9AENERGqvUUJpfHw8CxYscC2np6djt9vrPNp+8uTJTJ48WS2lIo0sPbeYF1ansnRnJs7KWd24+sK2TE2M5YK2QeYWJyIibq1RQumQIUOw2Wy8+eabTJgwgVmzZpGYmIi3t3edjqeWUpHGdeh4CS+uSeXjHZk4TqXRkT3b8GBiLL3a6z+GIiLy21mMqlns6/vAFgvp6elER0cDsGzZMsaNG0dAQABeXl6sW7eOnj17/qbPqGopLSgoIChIrTQi9e1IXgnz16bx0bYjVJwKoyMuiGRaYhy9OyqMiojI+dU0rzVYS+mvs+6YMWPYv38/27dvJyEhgfDw8Ib6aBH5jX4qOMn8tWl88O1hyh2Vf5eHxEUwLTGWizuFmlydiIh4okbpvq/Stm1brr322t98HHXfizSMbFspL6/bz7tbDlHmcAJwebdwpiXG0T9aT1wTEZGG02Dd941B3fci9SOn0M6rX+/n7c0HsVdUhtEBMWE8NDKOhC7q1RARkbozvfu+IamlVKR+HC+y89r6A7yVlEFpeWUY7dc5lOkj4xjYNRyLxWJyhSIi0lyopVSkGcovKWPBhgO8uSmDkrLK/9z1jQrhoZFxDIltrTAqIiL1xqNbSkWkbgpOlrNwYzpvbEynyF4BwIUdgnhoZBzDu0cqjIqIiGkUSkWagcLSct7clMGCDQcoLK0Moz3aBTEtMZaRPdsojIqIiOncMpTqnlKRmim2V7Dom8owml9SDkBcm5Y8mBjHVb3a4uWlMCoiIk2D7ikV8UAlZRUsTjrIv9Yf4ERxGQBdI1rwYGIc1/ZupzAqIiKNRveUijRDpeUO3t58kFe/3k9uUWUYjWndgqlXxDK6b3u8FUZFRKSJUigV8QCl5Q7e33qIl9ftJ7vQDkCnsECmXBHLdRe1x8fby+QKRUREzs0tQ6nuKRWpZK9w8OG2I8xfk0aWrRSADiEBPDCiGzf264ivwqiIiLgJ3VMq4obKHU6WbD/CS2vSyMw/CUC7YH8mD+/Gzf2j8PNRGBURkaZB95SKeKAKh5OPd2Ty4ppUDp+oDKORraxMHt6NW+Kj8Pf1NrlCERGRulEoFXEDDqfBsl2ZPL8qlYzjJQC0bunHpGHduPXSTgqjIiLi9hRKRZowp9Pgv7t/4vlV+9ifUwxAWAs/7h3ahdsSOhPop7/CIiLiGfQvmkgT5HQafPlDFvNW7WPfsSIAQgJ9uXtIF+4YGE0Lq/7qioiIZ3HLf9k0+l48lWEYfJVyjLkr97EnqxCAIH8f7hrchTsvj6aVv6/JFYqIiDQMjb4XaQIMw2DNnmzmrtpHcqYNgJZWH/4wKIb/HRRDcIDCqIiIuCeNvhdxA4Zh8PW+HOau3MeuIwUABPp5M+HyaO4a3IWQQD+TKxQREWkcCqUiJjAMg01px5m7ah/bD+YBEODrze2XdebuwV0Ib2k1uUIREZHGpVAq0sg2HzjOnJX72Jp+AgCrjxe/T+jMPUO7EtFKYVRERJonhVKRRvJtxgnmrtzHN/uPA+Dn7cX4Sztx37CuRAb5m1ydiIiIuUwPpfn5+dxyyy1UVFTQoUMHFi1ahJeXHpEonuO7Q3nMXbmPDam5APh6Wxgb34n7hnelXXCAydWJiIg0DaaH0nfeeYdHH32UoUOHctNNN7Ft2zYGDBhgdlkiv9n3R/KZu3Ifa/fmAODjZeGm/lFMHt6VjqGBJlcnIiLStDRIk2Rubi4xMTFkZGS41iUnJxMfH09oaCgzZsygaiaqyZMnM3ToUNd+ERERDVGSSKP54WgBE9/axpiXNrF2bw7eXhZu7t+RtX8cxuwbeiuQioiInEG9h9Lc3FxGjRpVLZDa7XZGjx5Nv3792LZtGykpKSxatKjafl999RXt2rUjJiamvksSaRR7smzcu3g7176wkVU/HsPLAjdc3IFVDw3l2f/Xl6gwhVEREZGzqffu+7FjxzJ+/Hi2bNniWrd8+XIKCgqYM2cOgYGBzJo1i8mTJzNhwgQAsrOzeeyxx1i+fPk5j22327Hb7a5lm81W3+WL1FrqsULmrU7l8+9/AsBigdF92jPlili6RbY0uToRERH3UO+hdMGCBcTExDB16lTXul27dpGQkEBgYGVLUZ8+fUhJSQEqg+Ytt9zC888/T3h4+DmPPXv2bJ566qn6LlmkTvbnFPHC6lSW7TpK1XPRru3djqmJscS1aWVucSIiIm6m3rvvz9T9brPZqq23WCx4e3uTl5fHG2+8wffff8/MmTMZNmwYa9asOeuxZ86cSUFBAf/85z/p3r073bp1q+/yRc7r4PFiHvpwJyPnfM3SnZWB9MpebVg+dTDzb71EgVRERKQOGmX0vY+PD1Zr9UnB/f39KSkpYdKkSUyaNKlGx7FarVitVqZPn8706dNdz1IVaQyHT5Tw0po0lnx3BIezsmk0sUckDybGcWEH/RyKiIj8Fo0SSsPCwkhOTq62rrCwED+/uj3Xe/78+cyfPx+Hw1Ef5YmcU2b+SeavTePDbw9TcSqMDusewbTEOPpGhZhbnIiIiIdolFAaHx/PggULXMvp6enY7XbCwsLqdLzJkyczefJktZRKg8oqKOXldWm8v/UwZQ4nAINjW/NgYhz9OoeaXJ2IiIhnaZRQOmTIEGw2G2+++SYTJkxg1qxZJCYm4u3tXafjqaVUGlJ2YSmvrNvPO1sOUVZRGUYTuoTx0MjuDIip23+kRERE5NwsRtUs9vV9YIuF9PR0oqOjAVi2bBnjxo0jICAALy8v1q1bR8+ePX/TZ1S1lBYUFBAUFFQPVUtzlltk519f72fx5oOUlleG0fjoUKaNjOOyrq1Nrk5ERMQ91TSvNVhL6a+z7pgxY9i/fz/bt28nISHhvNM/nYtaSqU+5RWX8a/1B3jrmwxOllf+TF3cKYSHRsYxqFtrLBaLyRWKiIh4vgZrKW0MaimV3yK/pIzXN6Tz5qZ0issqw2ifjsFMGxnHsLgIhVEREZF6YHpLqUhTZSst542N6SzckE6hvQKAnu2CeGhkHFf0iFQYFRERMYFbhlJ130tdFNkrWLQpndfWH8BWWhlGL2jbigcT4/j/7d1rVFNnvgbwJyEkEDDIHREKQaDWdtQWsXjDonh6oy7PdNWqHae1rbWWqVbXYk7tfJhxzRr7pRXtHHoZeqHHOXbaacfaGadjsVSqU9RKlYsRIQoKKgo0JgEkXPKeD0iOWMAQk+yQPL+1+LC3eTd/Xzd/HvebvXP/ndEMo0RERBLi8j15vQ5LL/6n7Cze+fY0rnT2AABSooLxUnYqHrwrBnI5wygREZGrcPmefN7V7j78+dBZvF16Gm0d3QCApIggrM9OQc7UWPgxjBIREXmMMRlKuXxPI+nq6cPOw+fw5v7TaG23AAASwtVYvzAFi6fFQuEnl7hCIiIiuhGX78lrWHr78PH3jSj4Ro9Lpv4wGhcaiHULU/DzuycyjBIREUmAy/fkM7p7rfhreSMKSvS4YOwCAMSGBODFhSl49J44KBUMo0RERJ6OoZTGrJ4+K/72QxPe+FqP81euAgBiNAHIXZCMpTPioFI49jG2RERE5H4MpTTm9PZZsfv4BbxRUoezbZ0AgMhxKuTeNwnLZt6GAH+GUSIiorFmTIZS3ujkm/qsAv+ovIDt++pwprUDABAepMTa+ybhFxkJDKNERERjGG90Io9ntQr8s/oitu2rg/5yOwAgVO2PNfMn4ZezEqBWjsn/WxEREfkE3uhEY57VKvCVrhn5xXU4dckMAAgJ9MdzmUl4cnYiglU8fYmIiLwFf6uTxxFCYN/Jy8gvroXuogkAMC5AgWfnJmHV3ERoAvwlrpCIiIicjaGUPIYQAvtPtSB/Xy0qm4wAgGCVAk/PScQzc5MQomYYJSIi8lYMpSQ5IQQO1LVia3EtjjdeAQColX54anYiVs9LQmiQUtoCiYiIyOXGZCjl3ffe4zt9fxg9etYAAAjwl+OXsxKxJjMJ4cEqiasjIiIid+Hd9ySJw2fakL+vFofO/AgAUCnk+EVGAtbMT0LUuACJqyMiIiJn4d335JHKz/6I/OI6HNS3AgCUfnIsnxmPF7KSEa1hGCUiIvJVDKXkFscbryC/uBaltS0AAH8/GZbOiEduVjJixwdKXB0RERFJzWNCaVtbGzIzM3HixAmpSyEnqj5vRH5xLb6uuQwA8JPL8FhaHHKzkhEfppa4OiIiIvIUHhFKzWYznnzySRgMBqlLISfRXTBh275afKW7BACQy4Cf3xOHFxckIyE8SOLqiIiIyNPIXXXg1tZWaLVaNDQ02PZVV1cjPT0doaGhyMvLw8A9VnK5HDt27ODNSl6g9pIZL/xvOR564wC+0l2CTAYsmR6LfRvn47XHpjGQEhER0ZBcEkpbW1uRk5MzKJBaLBY88sgjSEtLw9GjR6HT6VBUVAQACAoKQmhoqCtKITfRX27Hix8dw/3bvsU/q5ohkwE5UyegeEMmti27G0mRwVKXSERERB7MJcv3y5Ytw4oVK3D48GHbvi+//BJGoxFbt26FWq3Gli1bkJubi1WrVrmiBHKT+tYOvPF1HXYfPw/rtYeLPXhXDNZnp2ByDK98ExERkX1cEkoLCwuh1Wqxfv16276KigpkZGRAre6/uWXq1KnQ6XSjOq7FYoHFYrFtm0wm5xRMo3aurRN/LKnD346dR9+1NLpoSjReyk7BnbEhEldHREREY41LQqlWq/3JPpPJNGi/TCaDn58fDAaD3Uv3r776KjZv3uy0Omn0mgydKPhGj78ebULvtTC6YHIUNmSn4mdxDKNERETkGLfdfa9QKKBSDf7YyICAAHR2dtpCaU1NzYjH2LRpEzZu3GjbNplMiI+Pd36x9BMXjVdR8I0eH3/fiJ6+/jCamRqJDdkpuPs2vh+YiIiIbo3bQmlYWBiqq6sH7TObzVAqlXYfQ6VSQaVSoaCgAAUFBejr63N2mXSDS6YuvLX/NHYePofuPisAYE5yODZkp2JGYpjE1REREZG3cFsoTU9PR2FhoW27vr4eFosFYWGjDza5ubnIzc21fZYqOV+L2YK3S0/jz4fOwtLbH0ZnasOwcVEqMpLCJa6OiIiIvI3bQmlmZiZMJhM++OADrFq1Clu2bEF2djb8/PxGfSxeKXWdtnYL/vTtGXxY1oCunv4wmpYQio2LUjF7UjhkMpnEFRIREZE3komBJ9i74uAyGerr65GYmAgA+OKLL7B8+XIEBgZCLpdj//79mDJlisPHH7hSajQa+eD9W2To6EbhgTMo+q4Bnd39YX9aXAg2/sftyEyJYBglIiIih9ib11x6pfTGvLt48WKcPn0a5eXlyMjIQHi4Y8vAvFLqPMarPXjvwBm8/+8GtFt6AQB3TdRg46JUZN0exTBKREREbuHSK6WuxiuljjN39eCDfzeg8MAZmLv6w+jkmHHYuCgVi6ZEM4wSERGRU3jElVJX4ZVSx7VbevHhdw3407dnYLzaAwBIjQ7GhuxU3H9nDORyhlEiIiJyP14p9RGd3b3YUXYW73x7Bj92dAMAJkUG4aXsVDz8swkMo0REROQSXn2llOzX1dOHPx86i7dLT6O1vT+MaiOCsH5hCh6ZFgs/hlEiIiLyAGMylHL5/ua6evrwlyPnULD/NFrMFgBAfFgg1i1IwX/ePREKP7nEFRIRERH9Py7fexlLbx8+OdqEghI9mk1dAICJ4wPx4oJkPJoWB3+GUSIiInIjLt/7mJ4+Kz4tb8J/l+hx/spVAMCEkADkZiVj6Yx4KBUMo0REROS5xmQo5fL9/+vts+Jvx87jjyV1aPyxP4xGjVMhNysZj6fHI8B/9J+YRURERORuXL4fo/qsAl9UnMf2fXVoaOsEAEQEK7H2vmQ8ce9tDKNERETkEbh876X6rAJ7qi5i275anGnpAACEBSnx/Pwk/CIjAWol/0mJiIho7GGCGSOsVoF/nWjGtn21qL3UDgAYr/bHc5lJeHJWIoJU/KckIiKisWtMJhlfek+pEAJf6S4hv7gWNc1mAIAmQIHV85Lw1JxEjAvwl7hCIiIiolvH95R6KCEESmouY2txLU5cMAEAglUKPD1Xi2fmahESyDBKREREno/vKR2jhBAorW1BfnEtKpqMAAC10g+r5iRi9bwkjFcrJa6QiIiIyPkYSj2EEAL/1rdha/Ep/HDuCgAg0N8Pv5ydgDWZkxAWxDBKRERE3ouh1AMcOtOGrcW1OFL/IwBApZBjZUYC1syfhMhxKomrIyIiInI9hlIJfd/wI/KLa/Hd6TYAgFIhx4qZt+GF+yYhShMgcXVERERE7sNQKoEfzhmQX1yLA3WtAAB/PxmWpd+GF7ImYUJIoMTVEREREbnfmAylY/WRUJVNV5BfXItvTrUAABRyGR6bEY9fLUjGxPEMo0REROS7+EgoNzhxwYj84jrsO3kJAOAnl+HReybixQUpiA9TS1wdERERkevwkVAeoKbZhG3FdfjXiWYAgFwGLLl7ItYtSEFiRJDE1RERERF5DoZSF6i7ZMa2r+uwp/IiAEAmAxZPi8W6hSmYFBkscXVEREREnscjQunKlStx+vRprFy5EmvXrpW6HIedaWnH9q/r8EXFBQy8KeLhqRPw0sIUpESPk7Y4IiIiIg8meSj97LPPEB0djR07dmDJkiVYsWIFQkJCpC5rVM62deCNr/XYdawJ1mth9IE7Y7A+OwV3TPDc97oSEREReQq5Kw7a2toKrVaLhoYG277q6mqkp6cjNDQUeXl5GLi/qrS0FI8++igAYO7cuSgvL3dFSS7R+GMn/uvTSix4vRSf/dAfSLPviMY/XpyLt1emMZASERER2cnpobS1tRU5OTmDAqnFYsEjjzyCtLQ0HD16FDqdDkVFRQCAjo4OxMbGAgA0Gg0uX77s7JKc7sKVq3hlVxWyXtuPj482os8qkHV7JHbnzsG7T87AXRPH1pVeIiIiIqk5ffl+2bJlWLFiBQ4fPmzb9+WXX8JoNGLr1q1Qq9XYsmULcnNzsWrVKgQHB+Pq1asAgPb2dgQHe+6NQM3GLry5X4+/HGlEd58VADAvJQIvZaciLSFU4uqIiIiIxi6nh9LCwkJotVqsX7/etq+iogIZGRlQq/ufyTl16lTodDoAQFpaGg4ePIjJkyejoqICM2fOHPbYFosFFovFtm0ymZxd/rB2Hz+PvE8r0d3bH0ZnJYVjw6JUzNSGua0GIiIiIm/l9FCq1Wp/ss9kMg3aL5PJ4OfnB4PBgCVLliArKwtVVVW28DqcV199FZs3b3Z2yXaZHj8efVaB9MRQbFiUitmTIiSpg4iIiMgbueRGpxspFAqoVKpB+wICAtDZ2QmNRoO9e/dizpw5+Oabb6BQDJ+TN23aBKPRaPtqbGx0dek2CeFB2PvSPHyyZhYDKREREZGTueWRUGFhYaiurh60z2w2Q6lUAgAiIiKwdOnSmx5HpVJBpVKhoKAABQUF6Ovrc0m9w0mO4rNGiYiIiFzBLVdK09PTUVZWZtuur6+HxWJBWBjfj0lEREREbgqlmZmZMJlM+OCDDwAAW7ZsQXZ2Nvz8/Bw6Xm5uLnQ6Hb7//ntnlklEREREEnHL8r1CocC7776L5cuXIy8vD3K5HPv373f4eFIt3xMRERGRa8jEwEcruUFzczPKy8uRkZGB8PDwWz6eyWRCSEgIjEYjNBp+ehIRERGRp7E3r7nlSumAmJgYPPzww+78lkREREQ0BrjlPaXOVlBQgClTpiA9PV3qUoiIiIjICdy6fO9sXL4nIiIi8mz25jVeKSUiIiIiyfFKKRERERG5jFdfKSUiIiIi7+LWu++dbeAir8lkkrgSIiIiIhrKQE672eL8mAylAw/P7+7uBgDEx8dLXBERERERjcRsNiMkJGTYPx/T7ym1Wq24cOECxo0bB5lM5vLvZzKZEB8fj8bGRr6HdQScJ/twnuzDebIP58l+nCv7cJ7sw3m6OSEEzGYzYmNjIZcP/87RMXmldIBcLkdcXJzbv69Go+GJZwfOk304T/bhPNmH82Q/zpV9OE/24TyNbKQrpAN4oxMRERERSY6hlIiIiIgkx1A6CiqVCr/97W+hUqmkLsWjcZ7sw3myD+fJPpwn+3Gu7MN5sg/nyXnG9I1OREREROQdeKWUiIiIiCTHUEpEREREkmMoJSIiIiLJMZQSERERkeQYSq9TXV2N9PR0hIaGIi8v76af0QoAn376KRISEhAbG4uPPvrIDVVKb/fu3UhKSoJCocD06dNx8uTJm45ZvHgxZDKZ7Ss7O9sNlUpr3bp1g/7OycnJNx1TWlqKO+64AxEREdi6dasbqpReUVHRoHka+CoqKhpx3NSpUwe9/tlnn3VPwW7W2toKrVaLhoYG2z5HehXg3f1qqHlypFcB3t2vhponR3oV4N396sZ5crRPAb7Tq5xCkBBCiK6uLpGYmCjWrFkj9Hq9eOihh8T7778/4piqqiqhVCpFYWGhqKysFMnJyaKmpsZNFUtDr9eL0NBQ8fHHH4vm5mbx2GOPidmzZ9903IQJE0RVVZUwGAzCYDCI9vZ2N1QrrVmzZok9e/bY/s4mk2nE11++fFloNBqxefNmUVtbK+655x5RUlLipmqlY7FYbHNkMBhEY2OjiIiIEHq9ftgxHR0dQq1Wi8uXL9vGdXZ2urFq92hpaRH33nuvACDq6+uFEI71KiG8u18NNU+O9iohvLdfDTVPQoy+Vwnh3f1qqHlypE8J4Tu9ylkYSq/ZtWuXCA0NFR0dHUIIIY4fPy7mzJkz4pj169eL+++/37a9bds28Zvf/MaldUrt73//u3jnnXds2yUlJSIwMHDEMU1NTSImJsbVpXmUnp4eodFohNlstntMfn6+mDx5srBarUIIIT7//HPxxBNPuKpEj/WHP/xBrF69esTXHDx4UGRkZLipIuksXLhQbN++fdAvR0d6lRDe3a+GmidHepUQ3t2vhponR3qVEN7dr4aapxvZ06eE8J1e5Sxcvr+moqICGRkZUKvVAPovt+t0upuOWbBggW175syZKC8vd2mdUsvJycFzzz1n2z516hRSUlJGHHPkyBH09fUhLi4OQUFBWLZsGQwGg6tLlVRVVRWsViumT5+OwMBAPPDAAzh37tyIYyoqKpCVlQWZTAbAN86nG3V1dWH79u145ZVXRnzdkSNH0NTUhMjISIwfPx5r166FxWJxU5XuU1hYiHXr1g3a50ivGhjnrf1qqHlypFcB3t2vhponR3oV4N39aqh5up69fQrwnV7lLAyl15hMJmi1Wtu2TCaDn5/fiM3oxjEajQYXLlxwaZ2epLu7G6+//jqef/75EV9XU1ODadOmYc+ePTh06BDq6+uxadMmN1UpDZ1Oh9tvvx07duxAZWUlFArFoF+QQ/H18wkAdu7ciXvvvReJiYkjvu7UqVOYO3cuDh48iL1796K4uBj5+fnuKdKNrj8fBjjSq4Ya503n11DzdD17exXg3f1qqHlypFcBvn0+2dunAN/pVU4j9aVaT/HrX/9abNiwYdC+uLg40dTUNOyYmTNnit27d9u29Xq9SE5OdlmNnubll18W06ZNE93d3aMaV1paKsLDw11UlWc6e/askMvlwmg0DvuapUuXiu3bt9u2e3t7hUKhcEd5HiM9PV3s2bNn1OM+/PBDkZaW5oKKPAOuW0Z0pFcJ4Rv9CsMstzraq4Twzn413DwJYV+vEsI3+tVw8+RonxLC+3vVreKV0mvCwsLQ0tIyaJ/ZbIZSqbR7zM1e701KSkpQUFCAnTt3wt/ff1Rjo6Ki0NbW5lNLGFFRUbBarbh48eKwr/Hl8wkA9Ho99Ho9Fi1aNOqxUVFROH/+vAuq8jyO9KqhxvnK+XUrvQrwvX5lT68CfPd8upU+BfhWr3IEQ+k16enpKCsrs23X19fDYrEgLCzM7jHHjh3DxIkTXVqnJ6ivr8fy5ctRUFCAKVOm3PT1jz/+OA4ePGjbLisrQ3R0NFQqlSvLlFReXh527txp2y4rK4NcLkd8fPywY3z1fBrwySefICcnx67gMGvWLDQ2Ntq2y8rKkJCQ4MryPIYjvWqocb5wfo22VwG+168c6VWAb55PwOj6FODbvcohUl+q9RQ9PT0iMjLS9miVZ599VuTk5AghhDAYDKK3t/cnY44fPy6CgoJEZWWlMJvNYvr06eK1115za93u1tnZKaZMmSJWr14tzGaz7ctqtQqj0Tjk8tjvf/97MWPGDHHgwAGxa9cuER0dLX73u99JUL377NixQ2i1WrFv3z6xd+9ekZqaKp566ikhhBh2nlpaWkRAQIAoLi4W3d3d4oEHHhC/+tWv3F26ZObNmyfee++9QfuG+9l75plnxIMPPigOHTokioqKRFBQkCgqKnJXqW6HG+6WHq5XCeHb/er6eRqpVwkx/M+hL/Sr6+dppF4lhG/3KwyxfD9UnxKCvcpZGEqvs3v3bqFWq0V4eLiIjIwUJ06cEEL0n5jHjh0bcswrr7wilEql0Gg0Ii0tzeufP/b5558LAD/5qq+vFwkJCWLXrl0/GdPd3S2efvppERQUJGJiYsTmzZtFT0+P+4t3s5dfflmEhISIsLAwsW7dOtuzDoebJyGEeOutt4S/v78IDQ0VWq1WNDc3u7Fi6XR2dgqlUilOnjw5aP9wP3sGg0EsWbJEBAYGioSEBPHmm2+6qVJp3PjLcbheNfBaX+1X18/TSL1KiOF/Dn2hX914Pg3Xq4Tw7X514zwN16cGXstedetkQtj5USA+orm5GeXl5cjIyEB4eLhdY3Q6Hc6fP4/58+f7xHtqyLXq6+tRU1ODefPmITg4WOpyyEM50qsA9ityLvYrciaGUiIiIiKSHG90IiIiIiLJMZQSERERkeQYSomIiIhIcgylRERERCQ5hlIiIiIikhxDKRERERFJjqGUiIiIiCTHUEpEREREkmMoJSIiIiLJ/R/rPGtI6TfNMwAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = pd.Series(np.exp(np.arange(20)))\n",
    "plt.figure(figsize=(8, 9))\n",
    "ax1 = plt.subplot(2, 1, 1)\n",
    "x.plot(label='原始数据', legend=True)\n",
    "\n",
    "ax1 = plt.subplot(2, 1, 2)\n",
    "x.plot(logy=True, label='对数数据图', legend=True)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2024-05-23T11:29:08.491822Z",
     "end_time": "2024-05-23T11:29:09.802241Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values = np.array([1, 2, 3, 4, 5])\n",
    "y_values = np.array([5, 7, 3, 8, 4])\n",
    "y_error = np.array([0.5, 0.2, 0.8, 0.3, 0.6])\n",
    "\n",
    "# 绘制基础误差棒\n",
    "plt.errorbar(x_values, y_values, yerr=y_error, fmt='o', color='blue', ecolor='red', capsize=5)\n",
    "\n",
    "# 添加标题和标签\n",
    "plt.title('Basic Error Bar Plot')\n",
    "plt.xlabel('X-axis')\n",
    "plt.ylabel('Y-axis')\n",
    "plt.show()"
   ],
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     "start_time": "2024-05-23T11:29:09.327275Z",
     "end_time": "2024-05-23T11:29:09.874258Z"
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